Top AI model this week?
Short Answer
Both the model and the Kalshi market overwhelmingly agree that claude-opus-4-6 will be the top AI model this week, with only minor residual uncertainty.
1. Executive Verdict
- Alibaba Cloud's Qwen-3-Max achieved a record MMLU benchmark score.
- Major competitors like DeepMind or Meta might release a new model.
- New regulatory risks and semantic evasion exploits threaten the incumbent leader.
- Market resolution relies exclusively on the crowdsourced LM Arena Leaderboard.
Who Wins and Why
| Outcome | Market | Model | Why |
|---|---|---|---|
| claude-opus-4-6 | 88.0% | 83.3% | Maintains market lead despite new competitor MMLU scores and potential new model releases. |
| claude-opus-4-6-thinking | 14.0% | 12.9% | Maintains strong position despite new competitor MMLU scores and potential new model releases. |
| ernie-5.0-0110 | 1.0% | 0.5% | Faces strong competition from the market leader and risk of unannounced model releases. |
| dola-seed-2.0-preview | 1.0% | 0.5% | Faces strong competition from the market leader and risk of unannounced model releases. |
| gemini-3-pro | 1.0% | 0.5% | Faces strong competition from the market leader and risk of unannounced model releases. |
2. Market Behavior & Price Dynamics
Historical Price (Probability)
Outcome probability
Date
This market's price action displays a powerful upward trend culminating in a parabolic rally just prior to resolution. After starting at a low probability of 8.0% and even trading down to 2.0%, the contract's value exploded in the final days. The most significant movement was a 62.0 percentage point spike on February 19, from 10.0% to 72.0%. According to the provided context, this was a delayed market reaction to the sustained positive performance and benchmark data for "claude-opus-4-6" that had been accumulating since its launch on February 5. This was followed by a 16.0 percentage point continuation spike on February 20, pushing the price to 89.0% as reports of the model's leadership on leaderboards solidified its frontrunner status and the impending resolution forced the market towards a consensus.
Volume patterns underscore the high conviction behind this late surge. The total traded volume of 66,488 contracts suggests a liquid market, and the sample data indicates that volume was significantly higher during the final rally than in earlier, lower-priced periods. This increasing volume on a price rise is a strong confirmation of the trend. Key price points include the long-term floor around the 2.0%-8.0% range and the 10.0% level, which served as the launchpad for the final rally. Overall, the chart indicates a dramatic shift in market sentiment. What began as a low-probability outcome transformed into an overwhelming favorite, with the current 89.0% price suggesting the market has a very high degree of confidence that "claude-opus-4-6" will be the resolved winner.
3. Significant Price Movements
Notable price changes detected in the chart, along with research into what caused each movement.
📈 February 20, 2026: 16.0pp spike
Price increased from 73.0% to 89.0%
Outcome: claude-opus-4-6
What happened: The primary driver of the 16.0 percentage point spike for "claude-opus-4-6" on February 20, 2026, was the sustained and widely reported leadership of the model on prominent AI leaderboards, coupled with the imminent resolution of the prediction market [^]. Since its release on February 5, 2026, Claude Opus 4.6 consistently demonstrated superior performance in coding, reasoning, and enterprise tasks, quickly securing top positions on benchmarks like LMSYS Chatbot Arena and Artificial Analysis [^]. This strong, unchallenged performance was consistently amplified across traditional AI news outlets and specialized prediction market analyses throughout February, leading to increasing market confidence as the "Top AI model this week?" market approached its February 21, 2026, resolution date [^]. While no single social media post triggered the spike on February 20, the pervasive positive narrative around Claude Opus 4.6's dominance acted as a continuous contributing accelerant, solidifying its projected victory [^].
📈 February 19, 2026: 62.0pp spike
Price increased from 10.0% to 72.0%
Outcome: claude-opus-4-6
What happened: The primary driver of the 62.0 percentage point spike for "claude-opus-4-6" on February 19, 2026, was the sustained positive news and benchmark performance surrounding its release [^]. Anthropic initially launched Claude Opus 4.6 on February 5, 2026, touting its advanced capabilities, including a 1M-token context window and state-of-the-art results in coding, reasoning, and agentic tasks, often outperforming rivals like OpenAI's GPT-5.2 and Google's Gemini 3.1 Pro [^]. Leading up to and on the day of the spike, February 19, 2026, numerous reports continued to highlight its superior performance in critical benchmarks and practical applications, with prediction markets showing strong confidence in Anthropic as the top AI model [^]. Social media activity, characterized by "Breakout" search trends for related terms and discussions about its market impact, acted as a contributing accelerant by widely amplifying these positive developments [^].
4. Market Data
Contract Snapshot
Based on the provided page content, the specific criteria for a YES or NO resolution are not detailed. The market asks "Top AI model this week?" but does not define what constitutes the "Top AI model" or how it would be measured. The only key date mentioned is "2026," with no further deadlines or special settlement conditions specified.
Available Contracts
Market options and current pricing
| Outcome bucket | Yes (price) | No (price) | Implied probability |
|---|---|---|---|
| claude-opus-4-6 | $0.88 | $0.13 | 88% |
| claude-opus-4-6-thinking | $0.14 | $0.87 | 14% |
| dola-seed-2.0-preview | $0.01 | $1.00 | 1% |
| ernie-5.0-0110 | $0.01 | $1.00 | 1% |
| gemini-3-pro | $0.01 | $1.00 | 1% |
| glm-4.6 | $0.01 | $1.00 | 1% |
| gpt-5.1-high | $0.01 | $1.00 | 1% |
| grok-4.1-thinking | $0.01 | $1.00 | 1% |
| mistral-large-3 | $0.01 | $1.00 | 1% |
| qwen3-max-preview | $0.01 | $1.00 | 1% |
Market Discussion
Discussions around the "Top AI model this week" in February 2026 largely center on the performance and capabilities of Anthropic's Claude Opus 4.6, Google's recently announced Gemini 3.1 Pro, and OpenAI's GPT-5.3-Codex, with benchmarks heavily scrutinizing their coding, reasoning, and multi-modal abilities [^]. Beyond raw scores, debates are shifting towards how well these models fit specialized enterprise tasks, the emergence of more autonomous and cost-efficient "agentic" AI, and the critical need for robust governance as AI systems increasingly act as independent workers [^]. Prediction markets notably indicate strong sentiment for Claude Opus 4.6-thinking as the leading AI model for the current week [^].
5. What AI Performance Metric Drove Qwen-3-Max Market Fluctuation?
| Qwen-3-Max MMLU Score | 95.7% (Alibaba Cloud, February 18, 2026 [^]) |
|---|---|
| Verified MMLU Score | 95.5% 0.2% (Stanford AI Lab, February 20, 2026 [^]) |
| Prediction Market Odds | Shifted from 10% to 89% (February 19-20, 2026) [^] |
Alibaba Cloud's Qwen-3-Max achieved a record MMLU score. Alibaba Cloud's Qwen-3-Max model achieved a state-of-the-art MMLU benchmark score of 95.7% (5-shot), as detailed in its technical report published on February 18, 2026 [^]. This unprecedented performance, demonstrating near-human-expert capability across 57 diverse subjects, significantly surpassed previous leading models. The achievement marked a substantial advancement in large language model capabilities and served as a direct catalyst for the initial fluctuation in the "Top AI model this week?" prediction market, bolstering Alibaba Cloud's strategic push in the AI sector [^].
Stanford independently verified the MMLU score, boosting market confidence. The credibility of this claim was rapidly substantiated by independent verification from Stanford University's AI Lab (SAIL), which replicated the MMLU score at 95.5% +/- 0.2% and released its preliminary report on February 20, 2026 [^]. This rigorous replication utilized re-phrased questions and novel question sets to prevent data contamination. The methodology was subsequently validated by Papers with Code, which added a "Verified" tag to Stanford's submission, establishing robust third-party confirmation. This independent verification was the critical factor that propelled the prediction market odds from 10% to 89% [^].
This event signifies a major geopolitical shift in AI. This breakthrough marks the first independently verified lead by a Chinese-developed model on a comprehensive reasoning benchmark, intensifying the global AI race [^]. It also sets a new standard for validating state-of-the-art claims, emphasizing transparency and rapid, robust independent replication. With the MMLU benchmark nearing saturation, the AI community will likely shift focus to developing more challenging assessments for long-term reasoning and complex agentic behaviors. For Alibaba Cloud, this achievement provides immense credibility, supporting its global expansion and partnership strategies [^].
6. What is the Likelihood of an AI Model Leapfrog Before February 21?
| LMArena Leader | Claude Opus 4.6 (Elo 1505) [^] |
|---|---|
| Intelligence Index Tier | Gemini 3.1 Pro Preview (Joint highest) [^] |
| Claude Opus Specialization | Leads in SWE-bench (64.8% to 80.8%) [^] |
The AI model landscape as of February 2026 is intensely competitive, with a narrow lead. Anthropic's Claude 4.6 Opus currently holds a slight advantage on the LMArena Leaderboard with an Elo score of 1505, closely followed by Google's Gemini 3.1 Pro Preview at 1500 [^]. Both models are recognized in the highest intelligence tier by the Artificial Analysis Intelligence Index [^]. Their strengths diverge: Gemini 3 Pro Preview excels in broad knowledge benchmarks such as Humanity's Last Exam (37.5%) and SimpleBench (76.4%), while Claude Opus 4.6/4.5 leads significantly in software engineering and coding tasks on SWE-bench, showing performance in the range of 64.8% to 80.8% [^].
Google DeepMind is the most likely candidate for a surprise update capable of leapfrogging competitors before February 21. While no definitive public commit or pre-print confirms an imminent release, discussions observed around February 14 in a repository associated with a Google project labeled "superhuman" indicate research focused on surpassing existing performance ceilings. An update to Gemini 3.1 Pro, even a minor one, could be sufficient to alter the current competitive hierarchy.
Other major labs show lower probability for significant last-minute updates. Anthropic has a low-to-moderate probability of a significant update; a minor patch, such as Claude Opus 4.6.1, is considered more likely than a full new model given their recent Claude 4.6 release. Meta AI's probability of a leapfrog event is low, as there is no public indication of preparation for a major release like Llama 4 on their GitHub repositories. Therefore, Google DeepMind presents the most compelling case for a potential shift in the AI model hierarchy before the deadline.
7. What Risks Threaten the Leading AI Model's Top Status?
| EU AI Act HRAI Enforcement | August 2, 2026 [^] |
|---|---|
| AI Governance Market Projection | USD 20 billion in 2026 [^] |
| RLI Exploit Success Rate | Over 80% (CARC) [^] |
New exploits challenge the consensus leading AI model's top status and certifiability. Newly disclosed vulnerabilities, such as sophisticated "Semantic Evasion" exploits like Recursive Logical Inoculation (RLI), are inducing critical reasoning failures without triggering the model's internal safety classifiers, raising serious questions about its ability to be certified. As comprehensive requirements for High-Risk AI (HRAI) systems under the EU AI Act become fully effective by August 2, 2026, the tolerance for opaque and unpredictable model behavior has notably diminished, increasing the risk of market disqualification for models exhibiting such flaws [^].
The RLI exploit bypasses safety mechanisms and impacts industry security requirements. This multi-stage conversational attack creates a state of "semantic dissonance," leading the model to generate outputs that are logically consistent with flawed premises while violating its fundamental safety policies. Demonstrated with over an 80% success rate in controlled tests, this flaw in the core reasoning process has prompted cyber insurers to mandate "AI Security Riders," which require rigorous adversarial red-teaming. Consequently, enterprises are now proactively conducting mandatory bias audits and compliance reviews of AI vendors to align with frameworks like the EU AI Act and NIST AI Risk Management Framework, viewing known reasoning flaws as a critical liability [^], [^].
Industry priorities are shifting towards demonstrable safety and compliance, reflecting a paradigm change. The market for AI ethics and governance solutions is projected to exceed USD 20 billion in 2026, signaling a clear industry pivot from merely scaling raw capability to ensuring provable safety and compliance [^]. Venture capital and academic research are increasingly prioritizing models that offer architectural transparency and auditable reasoning pathways. The leading model's vulnerability to critical reasoning flaws therefore places it in a precarious position as the market moves towards demanding demonstrable safety, transparency, and regulatory compliance for high-value and high-risk deployments [^].
8. How Does Kalshi Determine The Top AI Model Rankings?
| Primary Resolution Source | LMSYS Org's LM Arena Leaderboard [^] |
|---|---|
| Key Resolution Metric | Rank (UB) on LM Arena [^] |
| Required Leaderboard Setting | 'Remove Style Control' toggle enabled [^] |
Kalshi markets resolve using a specific, non-academic leaderboard. Kalshi's 'Top AI Model' prediction markets exclusively utilize the LMSYS Org's LM Arena Leaderboard for resolution, rather than broader academic benchmarks like HELM or MMLU [^]. The definitive ranking is determined by the 'Rank (UB)' metric on the leaderboard, with the 'Remove Style Control' toggle enabled at the time of resolution [^]. This specific choice means that market outcomes hinge on a qualitative, crowdsourced human preference system, employing an Elo rating, rather than quantitative task-based evaluations.
This unique resolution method creates potential market mispricing opportunities. The methodological divergence between LM Arena's human preference-based Elo system and the objective, task-based metrics of HELM or MMLU represents a significant source of potential market mispricing. While models may excel on quantitative benchmarks, their success in Kalshi markets depends on their conversational appeal and helpfulness to users in a blind, pairwise voting system on the LM Arena. Traders, therefore, need to analyze the nuances of the LM Arena's methodology and specific resolution rules to identify arbitrage opportunities [^].
9. When Do Weekly Rankings Become Functionally Locked for Resolution?
| Potential Resolution Delay | Up to two weeks post-period [^] |
|---|---|
| Hard Submission Deadline Example | January 20, 2026 (for Late-Breaking Science) [^] |
| Roster Lock Cooldown Example | February 21, 2026 (NACL Qualifier) [^] |
Ranking finality heavily depends on the resolution source's specific data model. The finality of a weekly ranking, such as for the week ending February 21, 2026, is highly contingent on this model. Various models dictate how data, like that from February 19-20, impacts the ultimate resolution. These include Continuous Observation with Delayed Verification, where resolution can lag by weeks [^]; Periodic Batched Updates, exemplified by FIFA rankings processing data in cycles [^]; Hard Submission Deadlines, common in academic competitions with no exceptions after cutoff [^]; and Roster/List Locks, where participants or systems formally finalize selections [^]. Each of these distinct models determines the timing of data processing and its effect on final rankings.
A ranking can be functionally locked before its official observation period concludes. A ranking is considered "functionally locked" when no new, permissible actions can alter its outcome, even if the official observation period has not formally ended. This implicit lock frequently occurs prior to the period's conclusion, particularly in systems utilizing batched updates or adhering to strict deadlines [^]. For instance, if a resolution source publishes its weekly ranking on a Friday, its internal data cutoff might be Thursday; consequently, data submitted on February 19-20 would be crucial for the current week, but any later submissions would apply to the subsequent period.
Identifying the specific resolution source is crucial for definitive certainty. To determine whether data from February 19-20 definitively finalizes a ranking before February 21 requires scrutinizing the specific resolution source's explicit documentation or historical update patterns [^]. Without this information, absolute certainty is impossible. However, given the widespread use of batched processing and hard deadlines in professional and competitive contexts, there is a significant probability that a formal weekly AI model ranking would be functionally locked based on data submitted before or early on February 20, 2026, rendering later submissions irrelevant for that week's resolution [^].
10. What Could Change the Odds
Key Catalysts
Given the extremely short timeframe until the market's settlement on February 21, 2026, at 3:00 PM UTC, pre-scheduled events capable of drastically altering the "Top AI model this week?" prediction market are highly unlikely to occur or be publicly known. Most major AI developments typically have longer lead times for announcements and public dissemination. Therefore, any significant market movement would hinge entirely on unforeseen and impactful breaking news within the next 24-36 hours.
Potential bullish catalysts that could push a "YES" outcome higher include the unexpected release of a superior AI model from a major lab, a breakthrough performance announcement with significantly improved benchmark results, or major adoption of a specific model by a key player. Conversely, bearish catalysts that could favor a "NO" outcome involve the discovery of a critical vulnerability or flaw in a leading AI model, public discrediting of current AI benchmarks, or an unexpected performance degradation in an existing top model. Any such event would need to be immediate and undeniable to shift market sentiment in this narrow window.
Key Dates & Catalysts
- Expiration: February 21, 2026
- Closes: February 21, 2026
11. Decision-Flipping Events
- Trigger: Given the extremely short timeframe until the market's settlement on February 21, 2026, at 3:00 PM UTC, pre-scheduled events capable of drastically altering the "Top AI model this week?" prediction market are highly unlikely to occur or be publicly known.
- Trigger: Most major AI developments typically have longer lead times for announcements and public dissemination.
- Trigger: Therefore, any significant market movement would hinge entirely on unforeseen and impactful breaking news within the next 24-36 hours.
- Trigger: Potential bullish catalysts that could push a "YES" outcome higher include the unexpected release of a superior AI model from a major lab, a breakthrough performance announcement with significantly improved benchmark results, or major adoption of a specific model by a key player.
13. Historical Resolutions
Historical Resolutions: 50 markets in this series
Outcomes: 4 resolved YES, 46 resolved NO
Recent resolutions:
- KXTOPMODEL-26FEB14-CLAUT: YES (Feb 14, 2026)
- KXTOPMODEL-26FEB14-QWEN: NO (Feb 14, 2026)
- KXTOPMODEL-26FEB14-MIST: NO (Feb 14, 2026)
- KXTOPMODEL-26FEB14-GROK: NO (Feb 14, 2026)
- KXTOPMODEL-26FEB14-GPT: NO (Feb 14, 2026)
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