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aiqbench

Google DeepMind · model passport

Google: Gemini 3.7 Flash

gemini-3-7-flash
  • Cloud only
  • Proprietary licence
  • 1,048,576 context
  • Released 2026-10-09(first seen on LMArena)
13/27axes covered
Overall · LMArena
1,488#14 of 396
Best percentile
97.7GPQA Diamond
Cohort standing
75.3median 60.6

What the data says

Benchmarked on 13 of 27 tracked axes. Every figure below is the model's own published result on that board.

Strongest axes

  • 97.7 pct — GPQA Diamond (94.8%)
  • 97.3 pct — Vision Arena (1,297)
  • 96.7 pct — Overall (1,488)

Weakest axes

  • 4.3 pct — Terminal-Bench 4.0 (11.2%)

Uneven: 93.4 percentile points between its best and worst axis — 97.7 pct on GPQA Diamond versus 4.3 pct on Terminal-Bench 4.0.

  • GPQA Diamond97.7 pct94.8%Verify →
  • Vision Arena97.3 pct1,297Verify →
  • Overall96.7 pct1,488Verify →
  • Instruction following96.7 pct1,485Verify →
  • Hard prompts96 pct1,507Verify →
  • Coding90.8 pct1,518Verify →
  • Factuality Arena90.1 pct1,475Verify →
  • SimpleQA Verified89 pct69.2%Verify →
  • ARC-AGI-288.8 pct84.6%Verify →
  • AIME (math)84.5 pct97.2%Verify →
  • WebDev Arena81.3 pct1,591Verify →
  • Agent Arena41.8 pct-0.007Verify →
  • Terminal-Bench 4.04.3 pct11.2%Verify →
  • Search ArenaNot benchmarked
  • Document ArenaNot benchmarked
  • FrontierMathNot benchmarked
  • Humanity's Last ExamNot benchmarked
  • SimpleBenchNot benchmarked
  • LiveBenchNot benchmarked
  • BFCL v4 (function calling)Not benchmarked
  • SWE-bench Verified (live board)Not benchmarked
  • MMLU-Pro (Artificial Analysis)Not benchmarked
  • LiveCodeBench (Artificial Analysis)Not benchmarked
  • IFBench (Artificial Analysis)Not benchmarked
  • HHEM Hallucination (Vectara)Not benchmarked
  • SWE-bench VerifiedNot benchmarked
  • Terminal-BenchNot benchmarked

Percentiles are the model's standing within each board's own population. Axes marked "not benchmarked" have no published result for this model — that is an absence of data, not a low score.

How to run it

Use it hosted

API model IDgoogle/gemini-3.7-flash
Context length1,048,576 tokens
Max output65,536 tokens
Acceptstext, image, video, file, audio
Input price$0.75 per 1M tokens
Cached input price$0.07 per 1M tokens
Output price$3.75 per 1M tokens

API parameters this endpoint supports

Include reasoningMax tokensReasoningReasoning effortResponse formatSeedStop sequencesStructured outputsTemperatureTool choiceTool callingTop-p

Example request

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-3.7-flash","messages":[{"role":"user","content":"Hello"}]}'

View on OpenRouter →

Identifiers, limits and prices are synced from the upstream source shown above. Any field we haven't synced is left out entirely rather than guessed.

  • Gemini 3.7 Flash (High) stands at 75.3 (raw mean 81.2) — measured on 13 of 27 axes.

    standingtemplateVerify →

  • Gemini 3.7 Flash (High) stands at 75.3 versus a cohort median of 60.6 across 171 models released within 180 days — above the peer median.

    cohorttemplateVerify →

Every claim is a computed fact from the current board data, phrased by a low-temperature model call and rejected by a validation gate if any number is not in the source row. How the leaderboards work →