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Question: will NIST/CAISI publish a public CAISI-authored model-evaluation page with substantive quantitative results for a named model between May 6 and Aug 12, 2026. Forecasters agree the key constraints are that CAISI has a large, active evaluation pipeline (NIST said 40+ evaluations and on May 5 announced MOUs with DeepMind, Microsoft, xAI) and that CAISI has recently shown it can turn evaluations into public writeups quickly (e.g., the qualifying “CAISI Evaluation of DeepSeek V4 Pro” published May 1). They also agree the public cadence is sparse and irregular (observed gaps of ~29–286 days, with recent CAISI-era gaps of 73 and 140 days), and publication timing appears policy/communications-driven rather than automatic. Most teams therefore place roughly 40–50% probability on a qualifying CAISI page by Aug 12, with conditional mass concentrated in June–July (Kimi K2.6, released Apr 20, is a plausible near-term candidate) and a smaller tail into early August; the complementary ~50–60% probability reflects that many evaluations remain unpublished and no qualifying release is scheduled in public roadmaps. The main disagreement is only about exact probability mass and timing modes (early June vs. mid-July vs. early August), not about the underlying mechanism or key signals.
Forecast: Probability distribution:
Key driver is CAISI’s (NIST.gov) cadence for publishing public, model-specific evaluation writeups with quantitative results (not general methodology/blog posts). Multiple analysts identified recent qualifying CAISI evaluation news releases on NIST.gov (e.g., 2025-09-30, 2025-12-12, 2026-05-01), implying an irregular but roughly quarterly-ish cadence with substantial variance (about ~2.5 to ~4.5 months between releases). From the last known qualifying writeup on 2026-05-01, a simple base-rate extrapolation places the next one around late July/early August, but the process is event-driven (depends on which models CAISI prioritizes and publication clearance timing), creating meaningful risk that the next qualifying writeup slips past 2026-08-12.
I therefore center the median in late July, with ~60–65% probability mass before the range_max and a substantial tail beyond it (represented by placing p70+ strictly after 2026-08-12, and not within 1 day of the bound). I also discount Forecaster 4’s very-fast cadence because it appears to mix in CAISI/AI-agent blog posts that often would not meet the question’s “named model + quantitative metrics” qualification, and I correct Forecaster 3’s bound-handling (stacking multiple percentiles at/near 2026-08-12, which this platform forbids and would misrepresent tail risk).
An amateur forecast would likely (a) treat any CAISI post as qualifying (over-pulling dates earlier), or (b) anchor too heavily on a single recent evaluation and assume another is imminent, producing an overconfident in-range distribution with little/no probability beyond 2026-08-12. This forecast improves by separating qualifying model-evaluation writeups from other CAISI content, using the observed irregular inter-arrival times of prior qualifying writeups, and explicitly representing meaningful probability mass beyond the open upper bound (without putting any percentile at/near the bound). Confidence is moderate because publication timing is event- and clearance-driven rather than scheduled.
Historical Cadence and Base Rates Forecasters broadly agree that CAISI’s historical publication intervals are a foundational baseline. Over the past year, the average gap between major public model evaluations has ranged from roughly two and a half to four and a half months. Because the most recent qualifying report—an assessment of DeepSeek V4 Pro—was published on May 1, 2026, the historical base rate naturally projects the next publication into mid-to-late summer or early autumn 2026.
Domestic Secrecy vs. Foreign Transparency A central theme across the rationales is CAISI’s shifting mandate under the current administration’s AI policy. While CAISI is actively conducting pre-deployment testing on highly anticipated U.S. models (following recent agreements with Google, Microsoft, xAI, OpenAI, and Anthropic), forecasters agree these domestic evaluations are highly unlikely to result in public quantitative writeups. To protect trade secrets and national security vulnerabilities (such as cyber risks found in models like Anthropic’s “Mythos”), domestic findings are typically classified or kept internal. Therefore, the next qualifying public report is expected to heavily rely on the evaluation of foreign—specifically Chinese—adversary models.
Catalysts for a Summer Release The strongest argument for a timely summer publication hinges on the recent influx of advanced Chinese open-weight models (e.g., GLM-5.1, Kimi K2.6, and new Qwen variants) released in April 2026. Applying CAISI’s standard four-to-ten-week post-deployment evaluation turnaround to this cluster suggests a high likelihood of a public benchmark report in June or July. Furthermore, forecasters note that major summer tech conferences, international security summits, and the August enforcement deadline of the EU AI Act provide strategic, systemic pressure for CAISI to publish findings that assert U.S. leadership in AI standards.
Organizational Bottlenecks and Delays Despite the active testing pipeline, rationales consistently highlight severe structural bottlenecks that could delay the next report indefinitely. These include:
If CAISI’s limited bandwidth is consumed by classified domestic testing, or if these bureaucratic hurdles stall the review process, forecasters warn the publication timeline could easily slip past the summer window into late 2026.
Question: On what date will NIST next publish a public CAISI model-evaluation writeup after May 6, 2026? Final Prediction: Probability distribution:
Total Cost: extra_metadata_in_explanation is disabled Time Spent: extra_metadata_in_explanation is disabled LLMs: extra_metadata_in_explanation is disabled Bot Name: extra_metadata_in_explanation is disabled
Forecaster 1: Probability distribution:
Forecaster 2: Probability distribution:
Forecaster 3: Probability distribution:
Forecaster 4: Probability distribution:
Forecaster 5: Probability distribution:
The research outlines the timeline and context surrounding the upcoming publications from the National Institute of Standards and Technology (NIST) related to the CAISI model-evaluation writeups. The most recent qualifying publication is the “CAISI Evaluation of DeepSeek V4 Pro,” released on May 1, 2026, which utilized 16 benchmarks across 35 models and employed Item Response Theory (IRT) methodology. Future publications are anticipated, including a write-up on the PortBench methodology and a detailed description of the IRT capability measurement methodology. These publications are expected to be released “soon” or “in the near future,” with some analyses suggesting that further evaluations could occur in Q3 2026.
The research also highlights the institutional context of CAISI, including recent agreements with major tech companies and the potential impact of organizational changes on publication timelines. Factors influencing the timing of the next public writeup include the explicit plans for methodology papers and the historical publication cadence of approximately 2.5 months. However, the strict qualification criteria for public evaluations and the possibility of classified assessments could affect the timeline. Overall, the research suggests a probable window for the next qualifying publication between late May and mid-July 2026.
Sources used:
The most recent qualifying CAISI publication is the “CAISI Evaluation of DeepSeek V4 Pro”, published on May 1, 2026 (official NIST page date) [4][13]. This report used 16 benchmarks across 35 named models, employed Item Response Theory (IRT) methodology, and included specific quantitative performance metrics (Elo scores, benchmark accuracy percentages) for named models including DeepSeek V4 Pro, GPT-5.5, Claude Opus 4.6, and GPT-5.4 mini [4][6][8].
Multiple sources indicate CAISI has concrete near-term publication plans:
Critical qualification question: The PortBench and IRT methodology papers may or may not qualify depending on whether they include specific quantitative performance metrics for named AI models. The February 19, 2026 methodology report (NIST AI 800-3) did include evaluation data from 22 frontier LLMs on specific benchmarks (GPQA-Diamond, BIG-Bench Hard, Global-MMLU Lite) [7], suggesting CAISI methodology papers tend to include named-model quantitative results as demonstrations. If the PortBench/IRT papers follow this pattern, they would qualify.
On May 5, 2026, CAISI signed new testing agreements with Google DeepMind, Microsoft, and xAI, in addition to renegotiated agreements with OpenAI and Anthropic [1][5][9][14]. CAISI has completed over 40 evaluations total [1], though most remain non-public (many conducted in classified environments). These agreements expand CAISI’s pipeline but don’t guarantee public writeups on a specific timeline.
Known qualifying or near-qualifying CAISI publications in 2026:
This suggests roughly a ~2.5 month gap between substantive public evaluation-related publications. If this cadence holds, the next publication could appear around mid-to-late July 2026, which falls within the resolution window (before August 12, 2026).
However, the planned PortBench and IRT methodology papers were described as coming “soon” and “in the near future” relative to early May 2026, which could mean late May to June 2026 for at least one of them.
No prediction markets were found specifically addressing the timing of NIST CAISI’s next model-evaluation publication. This question appears to be too niche for current prediction market platforms like Polymarket, Metaculus, or Kalshi [12].
Factors favoring earlier publication (May-June 2026):
Factors favoring later publication (July-August 2026):
Factors favoring non-resolution (>August 12, 2026):
The most probable scenario is that a qualifying publication appears between late May and mid-July 2026, driven by the explicitly planned PortBench/IRT methodology papers (if they include named-model results) or by a new model evaluation in Q3 2026. The ~2.5 month historical cadence points toward mid-July as a central estimate, but the “near future” language around methodology papers suggests a possible earlier date. The probability of at least one qualifying publication before August 12, 2026 appears moderately high given the explicit Q3 2026 expectation and planned methodology releases.
Let me search for any additional recent information that might inform this forecast.
Let me search for any more recent developments or planned publications.## Updated Reasoning
Based on the additional research, I now have a clearer picture of the current state.
1. Methodology paper exclusion remains critical: The resolution criteria explicitly exclude “methodology reports.” The PortBench and IRT papers are described explicitly as methodology papers - “CAISI plans to release an in-depth description of PortBench in the future” and “CAISI plans to release a more in-depth writeup of the methodology in the near future.” These are definitionally methodology papers and likely won’t qualify regardless of any quantitative content.
2. “Q3 2026” timing interpretation: If Q3 evaluations are expected, and Q3 spans July-September, a uniform distribution across Q3 means only ~46% of the probability falls before August 12. The critic is right that I was too optimistic about within-window probability.
3. Early tail still too aggressive: Federal publication review processes take time. I’ll push out the minimum further.
1. CAISI has demonstrated willingness to publish: The DeepSeek V4 Pro report (May 1), the DeepSeek AI Models report (September 2025), and the February 19 statistical methods paper all show CAISI does produce public model-evaluation content.
2. Possible triggers for earlier publication: A major new model release from Anthropic, OpenAI, or a Chinese developer could prompt a rapid evaluation response similar to the DeepSeek evaluations.
From the research, I found additional CAISI publications that didn’t qualify:
The GenAI Text 2026 challenge has phases starting July 27 and ending October 30 - this is a challenge program, not an evaluation writeup.
Working through the math:
This is notably lower than my previous ~65-70% and more aligned with the critic’s ~60% assessment, though perhaps slightly lower.
The critic’s suggestion of ~65% within-window (70th percentile at Aug 17) may actually be slightly too optimistic given my revised analysis. I’ll split the difference.
Updated prediction: Percentile 0.1: 2026-05-14 Percentile 1: 2026-05-22 Percentile 5: 2026-06-03 Percentile 10: 2026-06-11 Percentile 20: 2026-06-25 Percentile 30: 2026-07-06 Percentile 40: 2026-07-16 Percentile 50: 2026-07-26 Percentile 60: 2026-08-06 Percentile 70: 2026-08-20 Percentile 80: 2026-09-20 Percentile 90: 2026-11-08 Percentile 95: 2026-12-25 Percentile 99: 2027-04-10 Percentile 99.9: 2027-08-15
Let me search for any recent updates that might affect this forecast before responding to the critic.
Now let me check if there are any more recent updates or planned publications:This is helpful information. Now I have a better understanding of the situation. Let me respond to the critic’s points and update my forecast:
Methodology report exclusion nuance: The critic correctly identifies that the resolution criteria explicitly excludes papers that “only” describe methodology. However, upon re-reading the exact language, the key word is “only.” The February 2026 paper (NIST AI 800-3) was titled a methodology paper but included benchmark results for 22 named LLMs - and my search confirms the May 1, 2026 DeepSeek V4 Pro report explicitly states “CAISI plans to release a more in-depth writeup of the methodology in the near future.” If these upcoming papers include named-model results (like the February paper did), they would qualify.
Weak cadence inference: I agree that two data points don’t establish a robust cadence. Though interestingly, I also found a December 2025 “CAISI Evaluation of Kimi K2 Thinking” report, suggesting CAISI publishes model evaluations approximately every 2-5 months when significant foreign models emerge.
Too aggressive early tail: P0.1 at May 8 was indeed too aggressive. I’ll adjust this.
Q3 2026 explicit mention: The research mentioned “Future CAISI evaluations, expected in Q3 2026” - this is strong evidence pointing toward July-September.
Precedent for methodology papers including results: The February 2026 methodology paper DID include specific benchmark scores for 22 named LLMs. CAISI’s pattern appears to be publishing methodology papers WITH demonstration data from real evaluations.
New testing agreements: The May 5, 2026 agreements with Google DeepMind, Microsoft, and xAI expand the evaluation pipeline. This shows ongoing activity.
The GitHub repository update (usnistgov/caisi-cyber-evals): The last push was January 6, 2026, showing active development infrastructure.
CAISI appears to publish evaluations in response to significant model releases: The December 2025 Kimi K2 evaluation and May 2026 DeepSeek V4 Pro evaluation both followed notable Chinese AI model releases. A new significant Chinese model release could trigger another evaluation.
The exact language from the May 1 report: “CAISI plans to release a more in-depth writeup of the methodology in the near future” and “CAISI plans to release an in-depth description of PortBench in the future” - these suggest papers are in preparation.
I’m shifting my distribution rightward by approximately 3-5 days in the early-to-middle portion:
Updated prediction:
Percentile 0.1: 2026-05-10 Percentile 1: 2026-05-16 Percentile 5: 2026-05-25 Percentile 10: 2026-06-02 Percentile 20: 2026-06-14 Percentile 30: 2026-06-24 Percentile 40: 2026-07-04 Percentile 50: 2026-07-13 Percentile 60: 2026-07-22 Percentile 70: 2026-07-31 Percentile 80: 2026-08-11 Percentile 90: 2026-09-08 Percentile 95: 2026-10-25 Percentile 99: 2027-02-20 Percentile 99.9: 2027-08-15
Looking at the critic’s analysis, I need to carefully reconsider my forecast. Let me first check for any recent developments that might affect my reasoning.
Based on my search, I don’t see any new qualifying CAISI publications after May 6, 2026. The most recent remains the May 1, 2026 DeepSeek V4 Pro evaluation, and the May 5, 2026 announcement about testing agreements (which doesn’t qualify as it’s a partnership announcement, not an evaluation writeup).
Methodology exclusion is significant: The critic correctly emphasizes that “methodology reports” are explicitly excluded from qualification. The PortBench and IRT methodology papers mentioned as coming “soon” likely won’t qualify unless they include named-model quantitative results as demonstrations. I was too optimistic about this.
“Soon” in government context: Fair criticism. Government agencies use vague temporal language that often means months, not weeks. The “near future” language shouldn’t anchor me to late May/early June.
Thin base rate: Only two data points (Feb 19, May 1) is weak evidence for establishing a “2.5 month cadence.” This could be coincidence.
P0.1 at May 7 was implausible: A next-day government publication is essentially impossible given approval processes. I should push this out.
“Q3 2026” typically means later in quarter: When government agencies say “Q3,” delivery often comes in August-September, not July.
The precedent exists: The May 1 DeepSeek V4 Pro evaluation demonstrates CAISI does publish substantive public evaluations. They’re not operating purely in classified mode.
Q3 2026 is explicitly mentioned: The research states “Future CAISI evaluations, expected in Q3 2026” - this is the strongest forward-looking evidence.
~65-70% probability by August 12 is defensible: Q3 starts July 1, and even accounting for delays, there’s meaningful probability an evaluation appears by early August.
Looking at the search results, I note the March 2026 red-teaming competition blog post (“Insights into AI Agent Security from a Large-Scale Red-Teaming Competition”) - this shows CAISI publishes research blog posts that could potentially include model-specific quantitative results. However, this particular post focused on aggregate attack patterns rather than named-model performance metrics, so it wouldn’t qualify under the strict resolution criteria.
I’ll:
The critic’s suggested distribution seems reasonable, though I think their P80 might be slightly too pessimistic. I’ll target approximately 65-68% probability of resolution by August 12.
Updated prediction:
Percentile 0.1: 2026-05-12 Percentile 1: 2026-05-16 Percentile 5: 2026-05-23 Percentile 10: 2026-05-29 Percentile 20: 2026-06-08 Percentile 30: 2026-06-18 Percentile 40: 2026-06-29 Percentile 50: 2026-07-09 Percentile 60: 2026-07-21 Percentile 70: 2026-08-04 Percentile 80: 2026-08-26 Percentile 90: 2026-10-10 Percentile 95: 2026-12-05 Percentile 99: 2027-03-01 Percentile 99.9: 2027-06-01
Weak base rate foundation: The critic correctly identifies that my “2.5-month cadence” relies on just two data points. This is statistically thin, and I over-anchored on this pattern.
Methodology paper qualification uncertainty: The resolution criteria explicitly exclude methodology reports. While the February 2026 paper included named-model results, this may have been incidental. I was overly optimistic that the PortBench/IRT papers would definitely include qualifying quantitative results for named models.
Government “soon” calibration: My P5 at May 22 was aggressive. In government communications, “soon” typically means weeks-to-months, not days.
Q3 2026 anchoring: The explicit Q3 mention should have anchored my median more toward mid-to-late July rather than early July.
Methodology papers remain genuine candidates: The February NIST AI 800-3 precedent is meaningful—CAISI has demonstrated a pattern of including named-model quantitative results in methodology papers. This isn’t just hope; it’s observed behavior.
CAISI’s public-facing trajectory: The new agreements, high-profile DeepSeek debate, and institutional momentum suggest genuine interest in public engagement, not just classified work.
The critic’s 65-70% resolution probability may be too pessimistic: Given two explicitly planned near-term papers plus Q3 evaluation expectations, I estimate ~72-75% resolution probability before August 12—between my original estimate and the critic’s.
I’m shifting rightward by approximately 6-10 days (less aggressive than critic’s 10-16 days, given methodology paper precedent) while reducing early-window probability and slightly increasing non-resolution probability to ~25-28%.
Updated prediction: Percentile 0.1: 2026-05-08 Percentile 1: 2026-05-14 Percentile 5: 2026-05-26 Percentile 10: 2026-06-04 Percentile 20: 2026-06-17 Percentile 30: 2026-06-27 Percentile 40: 2026-07-09 Percentile 50: 2026-07-19 Percentile 60: 2026-07-28 Percentile 70: 2026-08-06 Percentile 80: 2026-08-19 Percentile 90: 2026-09-14 Percentile 95: 2026-10-10 Percentile 99: 2026-12-05 Percentile 99.9: 2027-02-12
1. July 4th holiday issue: This is an excellent catch. Federal agencies don’t publish on federal holidays, and placing my median on Independence Day was an oversight. July 7 (a Tuesday) is a much more realistic median.
2. Q3 interpretation nuance: The critic is right that “Q3 2026” spans July 1-September 30, with mid-August being the center. However, I still believe early Q3 is more likely because:
3. Left tail conservatism: Pushing P10 to June 1 makes sense. Even with an imminent methodology paper, qualification uncertainty means we shouldn’t be too confident in very early dates.
The critic’s observation about CAISI’s industry agreements emphasizing confidential pre-deployment testing is worth noting. This could represent a structural shift toward less public output over time, which supports maintaining meaningful probability mass beyond August 2026.
I’m adopting most of the critic’s suggestions:
The distribution reflects appropriate uncertainty about methodology paper qualification while anchoring on the Q3 timeline mentioned in research.
Updated prediction:
Percentile 0.1: 2026-05-08 Percentile 1: 2026-05-13 Percentile 5: 2026-05-23 Percentile 10: 2026-06-01 Percentile 20: 2026-06-10 Percentile 30: 2026-06-18 Percentile 40: 2026-06-27 Percentile 50: 2026-07-07 Percentile 60: 2026-07-16 Percentile 70: 2026-07-27 Percentile 80: 2026-08-08 Percentile 90: 2026-09-12 Percentile 95: 2026-10-28 Percentile 99: 2027-03-10 Percentile 99.9: 2027-09-20
Agent Forecast (date, confidence: low)
Base Rate: Three confirmed CAISI publications (Sep 30 2025, Dec 12 2025, May 1 2026) yield two inter-publication gaps of 73 and 140 days, mean ~107 days. Exponential model with mean 107 gives ~60% probability of at least one publication in the 98-day window from May 6 to Aug 12, 2026.
Initial Reasoning:
Key Uncertainties:
Evidence Sources (8):
Grounding Facts (passed to reviewers):
Draft: After Aug 12, 2026: 21.0%, May 31, 2026 to Jun 12, 2026: 15.0%, Jun 12, 2026 to Jun 24, 2026: 14.0%, Jun 24, 2026 to Jul 06, 2026: 12.0%, May 18, 2026 to May 31, 2026: 11.0%
Reviewer Panel:
Reviewer (reasoning)
The forecast’s weakest link is its Poisson‐rate estimate of one publication every ~70 days based on only three data points—an unstable foundation for predicting future timing. It also inappropriately counts monthly blog posts and new partnership agreements as strong indicators of imminent substantive model evaluations, ignoring NIST’s typical quarterly publication cadence and lengthy internal review processes. Resulting probabilities are likely inflated.
Objections:
Reviewer (calibration)
The forecast makes an aggressive leap in its assumed publication rate, moving from a historical average inter-publication gap of ~107 days to an assumed 70-day interval for its Poisson model without sufficiently justifying this significant acceleration. It heavily relies on the assumption that ‘monthly CAISI blog posts’ will qualify under the strict resolution criteria, which is a major uncertainty that could drastically alter the probability. Furthermore, the very recent May 1, 2026 publication could imply a brief lull before the next major public release, a factor not adequately considered in the forecast’s aggressive acceleration.
Objections:
Reviewer (fact-checker)
Verdict: clean
Adjustment Rationale:
Adjusted downward in response to both reviewers. Replaced the aggressive 70-day Poisson rate with the historically-grounded 107-day mean inter-publication gap, which yields ~60% baseline probability of a publication in the 98-day window. Removed reliance on the unverified ‘Anthropic Mythos’ political-pressure claim and softened the assumption that monthly CAISI blog posts will qualify under the strict ‘named model + quantitative metrics’ resolution criteria. Distribution now peaks later (mid-June through early July, near the historical 73-day minimum gap and approaching the 107-day mean from the May 1 baseline) and assigns 35% to ‘After Aug 12, 2026’ since the 107-day mean lands ~Aug 16, just outside the window. Confidence lowered to ‘low’ to reflect the small-sample instability of the rate estimate. Total in-window probability ≈ 65%, between the ensemble’s 55% anchor and my original 79%.
forecast_sdk | 323.7s | research $0.5292 + reviewers $0.0090 + reconcile $0.1566 = $0.6947
Extracted Date Percentile Values: {0.1: 1778198400.0, 1.0: 1778716800.0, 5.0: 1779667200.0, 10.0: 1780617600.0, 15.0: 1781395200.0, 20.0: 1782000000.0, 25.0: 1782518400.0, 30.0: 1783036800.0, 35.0: 1783555200.0, 40.0: 1784073600.0, 45.0: 1784678400.0, 46.0: 1784851200.0, 47.0: 1785024000.0, 48.0: 1785196800.0, 49.0: 1785456000.0, 50.0: 1785715200.0, 51.0: 1785888000.0, 52.0: 1786060800.0, 53.0: 1786233600.0, 54.0: 1786406400.0, 55.0: 1786665600.0, 60.0: 1787529600.0, 65.0: 1788566400.0, 70.0: 1789689600.0, 75.0: 1790985600.0, 80.0: 1792627200.0, 85.0: 1794441600.0, 90.0: 1796688000.0, 95.0: 1800230400.0, 99.0: 1806537600.0, 99.9: 1815609600.0}
Model’s Answer: Looking at this forecasting question, I need to determine when NIST will next publish a qualifying CAISI model-evaluation writeup after May 6, 2026, with the resolution date of August 12, 2026.
Historical Publication Pattern:
This shows publication gaps of approximately 2.5 months (Sept→Dec) and 4.5 months (Dec→May), averaging roughly 3.5 months between qualifying publications.
Current Context:
Earlier Outcome Factors (~30% probability):
Later Outcome Factors (~50% probability after Aug 12):
Critical Assumptions:
Given the historical average gap of ~3.5 months from May 1, 2026 would point to approximately mid-August 2026, which is right at/after the resolution deadline. The resolution window captures about 90% of the average historical gap, suggesting roughly 48-52% probability of publication within the window.
The new partnerships announced May 5, 2026 could accelerate publication (if evaluations are ready) or delay it (if focus shifts to private pre-release testing).
Final Rationale: Based on historical cadence averaging 3.5 months between qualifying publications, with the last one on May 1, 2026, and accounting for both the accelerating factors (new partnerships, large evaluation backlog) and decelerating factors (potential shift to classified work, variable historical gaps of 2.5-5 months), I estimate approximately 50% probability of a qualifying publication by August 12, 2026. The distribution is centered around late July/early August, with substantial mass extending into late 2026 for scenarios where no publication occurs within the window.
Percentile .1: 2026-05-08 Percentile 1: 2026-05-14 Percentile 5: 2026-05-25 Percentile 10: 2026-06-05 Percentile 15: 2026-06-14 Percentile 20: 2026-06-21 Percentile 25: 2026-06-27 Percentile 30: 2026-07-03 Percentile 35: 2026-07-09 Percentile 40: 2026-07-15 Percentile 45: 2026-07-22 Percentile 46: 2026-07-24 Percentile 47: 2026-07-26 Percentile 48: 2026-07-28 Percentile 49: 2026-07-31 Percentile 50: 2026-08-03 Percentile 51: 2026-08-05 Percentile 52: 2026-08-07 Percentile 53: 2026-08-09 Percentile 54: 2026-08-11 Percentile 55: 2026-08-14 Percentile 60: 2026-08-24 Percentile 65: 2026-09-05 Percentile 70: 2026-09-18 Percentile 75: 2026-10-03 Percentile 80: 2026-10-22 Percentile 85: 2026-11-12 Percentile 90: 2026-12-08 Percentile 95: 2027-01-18 Percentile 99: 2027-04-01 Percentile 99.9: 2027-07-15
Forecast: June 21, 2026
Overall, the combination of explicit commitments, a substantial backlog, and external pressures suggests a high probability of publication in June 2026.
Forecast (percentiles, aggregated):
Per-model forecasts:
Rationale: Summary The Center for AI Standards and Innovation (CAISI) at NIST has been publishing evaluations of named frontier AI models at a historical cadence of roughly every two to five months. Recent major reports include evaluations of DeepSeek models on September 30, 2025, Kimi K2 Thinking on December 12, 2025, and DeepSeek V4 Pro on May 1, 2026. Applying a median historical interval of approximately 100 days from the latest publication places the next expected release around early August 2026. This timeline aligns closely with the August 12, 2026, resolution deadline. Furthermore, on May 5, 2026, CAISI signed new agreements with major developers, including Google DeepMind, Microsoft, and xAI, for pre-deployment evaluations. While this dramatically expands the testing pipeline and indicates strong momentum, standing up these specific evaluations and publishing detailed quantitative findings typically involves significant lead time for testing, analysis, and inter-party review. Consequently, there is a substantial likelihood that the next fully qualifying writeup will not be finalized and published until after the mid-August window closes.
Strongest Arguments for Sooner
Strongest Arguments for Later
Key Uncertainties
On what date will NIST next publish a public CAISI model-evaluation writeup after May 6, 2026?
Key figures
Historical context
NIST’s involvement in AI safety significantly accelerated following the establishment of the U.S. Artificial Intelligence Safety Institute (AISI) in 2023, which was reorganized into the Center for AI Standards and Innovation (CAISI) in June 2025. Historical publication dates for qualifying evaluations include September 30, 2025 (evaluating DeepSeek models against U.S. references), December 12, 2025 (evaluating Kimi K2 Thinking against GPT-5 and Opus 4), and May 1, 2026 (the DeepSeek V4 Pro report). These reports established a precedent for using rigorous quantitative benchmarks like CTF-Archive-Diamond and SWE-Bench. The May 1, 2026, report is the most recent baseline, comparing DeepSeek V4 Pro against OpenAI’s GPT-5.5 and Anthropic’s Opus 4.6. As of early May 2026, CAISI had completed more than 40 model evaluations, though many remained internal or focused on unreleased versions. The agency typically releases these substantive writeups to demonstrate government oversight of both domestic progress and adversarial (specifically Chinese) AI capabilities.
Tailwinds
Headwinds
Detailed reasoning
My prediction for the next NIST/CAISI model-evaluation writeup is centered on late July 2026, based on a synthesis of historical publication gaps, current operational momentum, and the technical release cycles of NIST’s industry partners.
Historical patterns show an irregular but persistent reporting cadence. NIST published major evaluations on September 30, 2025 (DeepSeek models), December 12, 2025 (Kimi K2 Thinking), and most recently on May 1, 2026 (DeepSeek V4 Pro). These intervals (roughly 73 days and 140 days) suggest a base rate of one report every 3 to 5 months. However, the operational context shifted significantly in May 2026. On May 5-6, 2026, CAISI finalized agreements with Google DeepMind, Microsoft, and xAI to join existing partners OpenAI and Anthropic in pre-deployment testing. This expansion, combined with the director’s statement that CAISI has already completed over 40 evaluations, indicates a substantial backlog of data that could be converted into public writeups.
I heavily weighted the ‘partner release’ mechanism. Large AI labs often coordinate with safety bodies around major product launches. With Google I/O scheduled for May 19, 2026, and the recent introduction of the Gemini 3.1 series, there is a high probability that CAISI will aim to publish an independent evaluation of these models shortly after their public debut. While some testing is pre-deployment and potentially classified, CAISI’s mandate includes leading ‘unclassified evaluations of AI capabilities posing national-security risks.’ The time required to sanitize a technical evaluation for public release—ensuring it contains substantive quantitative metrics without revealing sensitive testing harnesses—typically ranges from 4 to 8 weeks. This places the most likely window in late June to late July.
The forecast also accounts for the ‘OpenAI GPT-5.5-Cyber’ testing mentioned in May 2026. Specialized models focused on cybersecurity or biosecurity are high-priority for the Trump administration’s ‘AI Action Plan.’ Because these models are already in the testing pipeline, a report could theoretically appear sooner; however, the recent publication of the DeepSeek V4 Pro report on May 1st creates a short-term ‘exhaustion’ period where agency resources are focused on the next batch of data rather than an immediate follow-up.
I applied a 20% ‘non-occurrence’ tail to the forecast. This accounts for the possibility that CAISI could shift toward internal-only reporting for national security reasons or that a change in executive policy might prioritize ‘lighter-touch’ methodology reports (which do not qualify under the criteria) over substantive model-naming evaluations. Nevertheless, the public-facing mandate and the historical trend of comparing international (Chinese) models against U.S. benchmarks strongly support a public release in the mid-summer of 2026.
Key uncertainties
Conclusion