The hottest supermodels of May 2026.

The lab's verdict

Gemini 3.1 Pro Preview on Thinking-High is the only model to clear 45% on Humanity's Last Exam at this cutoff (46.44%). It is also the cheapest frontier model on the leaderboard at $1.74/M tokens and runs at 138 tokens/sec. There is no other model where the math is this clean.

Real-user sentiment, filtered

Researchers running their own brutal evals report it as the model that 'actually thinks' instead of pattern-matching. Critics note its safety filters still over-fire on technical prompts, and it has the worst voice-personality of the top three — it sounds like a textbook. Nobody who has tested it on reasoning rates it second.

The lab's verdict

Opus 4.7-Thinking holds the #1 to #4 positions on LMArena ELO (1494–1503) — three of four top slots are Anthropic models. Opus 4.8 leads the Artificial Analysis Intelligence Index at 61. On hardest-eval (HLE) it lands at 36.20% — behind Gemini 3.1 Pro and the GPT-5.4-Pro tier. The trade is real: it is the model people choose when given the choice, and it is not the model that wins the impossible-question benchmark.

Real-user sentiment, filtered

The model researchers reach for when the task is open-ended, the writing has to read, or the user is going to keep talking. Reliable refusals, calibrated uncertainty, the lowest sycophancy rate at the top tier per independent audits. The complaint is speed: 50 tok/s is slow next to Gemini 3.5 Flash at 187.

The lab's verdict

GPT-5 holds Aider Polyglot at 88.0% — meaning when a real-world editing benchmark grades real-world coding tasks, no other model beats it. GPT-5.4-Pro is the #2 model on HLE at 44.32%. GPT-5.5 xhigh is at AA Intelligence 60 (between Opus 4.8 and Opus 4.7). The catch: it shifts behavior between snapshot dates more than the other two; if reproducibility matters, pin the date.

Real-user sentiment, filtered

Worship from the engineering crowd. The Codex variant ships diffs that compile. Skepticism from the safety crowd — refusals still hallucinate threats on benign prompts, and the personality drifts under load. The post-training cadence is fast: today's GPT-5.5 is not last quarter's GPT-5.5.

The lab's verdict

Muse Spark posted 40.56% on Humanity's Last Exam — ahead of Gemini 3 Pro Preview and the GPT-5.4-XHigh tier. It also crossed 1489 LMArena ELO, top-5 in the world. It is the model nobody on Western Twitter was talking about until the leaderboards updated.

Real-user sentiment, filtered

Chinese-research community has been quietly evaluating it for weeks; Western reaction is still catching up. Public criticism focuses on training-data transparency and on whether the HLE score reflects genuine generalization vs eval-set leakage; the leaderboard methodology is taking that seriously. The model itself reasons sharply on Chinese-language tasks and slightly less so on English at the same prompt.

The lab's verdict

Qwen 3.7 Max lands at AA Intelligence Index 57 — tied with Gemini 3.1 Pro Preview and Claude Opus 4.7 max. It runs at 167 tokens/sec and costs $1.43/M. It is also the strongest reasoner of any model with an openly published weight family. The trade is that 'Max Preview' is a hosted API; the open-weight siblings (Plus, Standard) are one tier down.

Real-user sentiment, filtered

r/LocalLLaMA has been running it head-to-head against Opus 4.7 on agentic loops and reports it surprises. Western enterprise procurement hesitates on Chinese-vendor data-residency questions; that's a real concern, not a hype-filter dismissal. The community sentiment is: this is what frontier looks like when the price floor drops.

The lab's verdict

Grok 4.3 High posts 79.6% on Aider Polyglot — eighth in the world, ahead of every model except the GPT-5 / o3 / Gemini-2.5-Pro cluster. It runs at 158 tokens/sec at $0.64/M. The differentiator is what xAI does NOT filter — Grok answers questions other frontier labs refuse, with the corollary risk that those refusals existed for reasons.

Real-user sentiment, filtered

Loved by the build-it-now crowd. Distrusted by safety researchers for the same reason. The benchmark numbers are real; the question is what shows up in production when the safety floor is lower. Twitter-native users report it as fast and willing.

The lab's verdict

Gemini 3.5 Flash holds 1476 LMArena ELO (top-10) at $1.31/M and 187 tok/s. It is the model that disproves the premise that 'cheap = dumb.' The Intelligence Index sits at 55 — meaningfully below the S-tier, but with throughput and cost that the S-tier cannot touch.

Real-user sentiment, filtered

The model engineers actually use when the bill is real and the latency budget is tight. Acknowledged trade: it loses to Opus 4.7 on anything requiring sustained reasoning past about four turns, and to Gemini 3.1 Pro on the hardest math.

The lab's verdict

Kimi K2.6 at Intelligence Index 54 for seventy cents per million tokens is the most price-disruptive model on the leaderboard. It runs at 44 tok/s — the slowest in the top-15 — so it is a batch tool, not a chat tool. The trade is fully transparent: thinking quality near the frontier, throughput well below it, price an order of magnitude cheaper.

Real-user sentiment, filtered

Quietly adopted by researchers running their own academic-grade comparisons. The Chinese-research community evaluates Kimi alongside Qwen and GLM as a real competitive set; that triangulation does not exist in the same way in Western labs.

The lab's verdict

MiniMax-M3 posts AA Intelligence 55 — same tier as Gemini 3.5 Flash, with pricing and speed information not yet fully published on the major dashboards at the cutoff date. The lab is including it because the score is real, not because there is hype to ride.

Real-user sentiment, filtered

Underweight in Western coverage relative to the eval result. The model is a real competitor; the marketing apparatus around it is smaller than the actual technical position justifies.

The lab's verdict

Xiaomi posting an AA Intelligence Index of 54 at $0.18 per million tokens is the most disorienting line in the May 2026 leaderboard. That price is roughly an order of magnitude under the open-weight equivalent and two under the closed-weight S-tier. Either the price is subsidized, the score is overfit, or both — but the lab does not get to assume which without evidence.

Real-user sentiment, filtered

Skepticism is the right default until independent replication closes. The lab is including MiMo on the list at B-tier because the public eval is real and worth a hard look, not because the lab endorses the result without that look.

The lab's verdict

GPT-5.3 Codex at AA Intelligence Index 54 and 81 tok/s exists because the specialized variant beats the generalist on code-specific evals at lower latency and lower cost ($1.87/M). It is the model engineering teams reach for when the task is specifically code editing in a real repo, where the generalist's headroom on philosophy and writing doesn't matter.

Real-user sentiment, filtered

Adopted by the Cursor / Continue / Aider / Claude Code crowd as a fallback option when the generalist gets distracted. Not a chat model — do not put it in front of a customer.

The lab's verdict

DeepSeek's current public release did not crack the top-15 of any single leaderboard the lab pulled for this issue. That is a real fact and worth saying plainly. The reason DeepSeek is still on the watch list is that the next release in the R-series is widely anticipated by the open-weight community to close the gap, and the lab does not write off a lab that previously delivered a frontier-class open release.

Real-user sentiment, filtered

The community remains positive on DeepSeek's trajectory. The May 2026 leaderboards do not show it at the front; the next snapshot might. Watch.