Gemini 3.7 Flash (High)
Context 1M tokens
Top 2 cheapest providers (Adjusted $/task)
The same list price can give a different adjusted $/task (caching, token efficiency) — click a price for its inputs.
Within the active global provider, residency and confidentiality filters.
| # | Provider | Price channel | Raw input $/1M | Raw output $/1M | Adjusted $/task |
|---|---|---|---|---|---|
| 1 | Googlevia OpenRouter — Price via OpenRouter: OpenRouter's price for Google's endpoint (https://openrouter.ai/google/gemini-3.7-flash/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Google's endpoint (https://openrouter.ai/google/gemini-3.7-flash/providers), collected 2026-11-03. | $0.750 | $3.75 | |
| 2 | Google Vertex AIdirect — Direct price: Google Vertex AI's own price list (https://cloud.google.com/vertex-ai/generative-ai/pricing), collected 2026-11-03. | direct — Direct price: Google Vertex AI's own price list (https://cloud.google.com/vertex-ai/generative-ai/pricing), collected 2026-11-03. | $0.750 | $3.75 |
Composite
7 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one49.7
includes −15.4 for its Benchmaxxing signal (from 65.1; why, switch off in Options)
Benchmaxxing signal +15.4, very strong Benchmaxxing tag · very strong report →
AA Coding v4.x 76.1Coding Agent v1.4 58.1AA Intelligence (est.) 29.1AA Agentic 36.4Epoch ECI 158.2Software ECI 158.0DesignArena 1209/1209
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
48 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
5 of 53 values are Google's own claims (†), not independent measurements; a matching independent result replaces a claim as soon as one exists.
- Epoch ECI · attached
- Software ECI · attached
- DesignArena Web Apps (agentic) · attached
- DesignArena Full-Stack · attached
Agentic
AA-AnalystAgent10060.0%
AA-AnalystAgent published 2026-09-10 → · Published board — Tests analyst tasks using agentic Python execution across fourteen domains.
AA-Briefcase621,116 Elo
AA-Briefcase published 2026-09-10 → · Published board — Tests multi-week professional knowledge-work projects with linked tasks and large source collections.
GDPval-AA v2821,433 Elo
GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
Harvey LAB-AA6890.7%
Harvey LAB-AA published 2026-09-10 → · Published board — Tests legal-work deliverables across practice areas on Harvey's private task set. Artificial Analysis' run, graded by one LLM judge against task rubrics — not the same run or scale as Vals AI's HLAB row.
Terminal-Bench v2.1 (AA)9185.8%
Terminal-Bench v2.1 (AA) v2.1 → · Published board — Tests terminal-based work on the 89-task verified refresh using Terminus 2.
Terminal-Bench v4.0 (AA)7513.6%
Terminal-Bench v4.0 (AA) v4.0 → · Published board — Tests terminal-based work on the 66-task release using mini-SWE-agent v2.4.6.
ApprenticeBench API (NeoCognition)6932.0%
ApprenticeBench API (NeoCognition) published 2026-09-14 → · Claude Code — An agent completes the same 100 sequential accounts-payable tasks in the Odoo ERP with diminishing mentoring, using dedicated application API calls instead of the screen interface.
RSI-Exam 0.1 (aiming-lab)no percentile0.31
RSI-Exam 0.1 (aiming-lab) v0.1 → · Antigravity CLI — An agent spends a long, budgeted run improving an inherited, working-but-weak executable research method or harness on a visible split, and the single artifact it submits is re-run once on a sealed hidden split across 88 executable research tasks in six domains.
Terminal-Bench v4.0developer's claim11.2%† self-reported by the developer
Terminal-Bench v4.0 → · mini-SWE-agent — A benchmark to measure and evolve with the frontier of agent work, whose homepage leaderboard reports resolution rate on Terminal-Bench 4.0 tasks.
Finance Agent v2 (Vals Index v2)9259.0%
Finance Agent v2 (Vals Index v2) v2 → · Published board — Multi-step financial reasoning tasks.
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)628.8%
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2) v2 → · Published board — Long-horizon legal work product creation. The index column is Harvey's Legal Agent Benchmark's own published standalone score, reported as accuracy — not comparable with Artificial Analysis' Harvey LAB-AA row.
Terminal-Bench 2.1 (Vals Index v2)6977.5%
Terminal-Bench 2.1 (Vals Index v2) v2 → · Published board — Command-line interface problem solving; the page states that each index column is that benchmark's own published standalone score, so the runner is not asserted here.
Vals Index v2 (Vals AI)5459.3%
Vals Index v2 (Vals AI) v2 → · Published board — GDP-weighted average of agentic model performance across finance, coding and legal tasks.
AA Agentic Index7636.4
AA Agentic Index published 2026-09-18 → · Published board — Artificial Analysis publishes one Agentic Index per model, measured on its primary configuration and relayed by OpenRouter's Benchmarks API; the value is attached at family scope on the deterministic representative. Artificial Analysis publishes this board without a version number; we keep the date each result was retained.
Coding
Artificial Analysis Coding Agent Index v1.4no percentile56.6%
Artificial Analysis Coding Agent Index v1.4 v1.4 → · Antigravity SDK v0.1.8 — The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.
Artificial Analysis Coding Agent Index v1.48059.6%
Artificial Analysis Coding Agent Index v1.4 v1.4 → · Opencode — The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.
SciCode (AA subproblems) v1.0.18957.2%
SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.
DeepSWE (Datacurve, via Epoch AI)5865.3%
DeepSWE (Datacurve, via Epoch AI) published 2026-09-15 → · mini-SWE-agent — Pass rate of coding agents on original, long-horizon software engineering tasks, run by Datacurve with the mini-swe-agent harness.
FrontierCode 1.1 Main (Cognition)developer's claim42.2%† self-reported by the developer
FrontierCode 1.1 Main (Cognition) v1.1 → · chisel — Whether a maintainer would merge the agent's pull request, on tasks crafted by open-source maintainers and graded with tests, rubrics and verifiers.
FrontierSWE v22920.3%
FrontierSWE v2 v2 → · proximus — 34 hand-written real-world software tasks: every model is evaluated with the site’s own Proximus harness at its maximum reasoning effort, 5 trials per task under a 20-hour budget, scored by the site’s own review protocol; the headline value is mean@5 in percent with best@5/worst@5 bounds.
Code Migration (Vals Index v2 subset)2829.0%
Code Migration (Vals Index v2 subset) v2 → · Published board — Porting projects to another language, including COBOL modernization.
Vibe Code Bench (Vals Index v2)3770.4%
Vibe Code Bench (Vals Index v2) v2 → · Published board — End-to-end app-building tasks.
FrontierCode 1.1 Extended (Cognition)developer's claim54.7%† self-reported by the developer
FrontierCode 1.1 Extended (Cognition) v1.1 → · chisel — Whether a maintainer would merge the agent's pull request, on the full 150-task FrontierCode set crafted by open-source maintainers and graded with tests, rubrics and verifiers.
AA Coding Index v4.x · frozen 2026-10-279276.1
AA Coding Index v4.x · frozen 2026-10-27 → · Published board — Artificial Analysis withdrew the Coding Index with Intelligence Index v5.0 (2026-10-28). These are the last v4.x values, frozen with their own date (2026-10-27).
DesignArena Web Apps (agentic)611,209 Elo
DesignArena Web Apps (agentic) published 2026-11-03 → · Published board — Published Elo. Exact source attachment is retained; fewer than 200 battles excludes a row from radar normalization and anomaly peers.
DesignArena Full-Stack601,209 Elo
DesignArena Full-Stack published 2026-11-03 → · Published board — Published Elo. Exact source attachment is retained; fewer than 200 battles excludes a row from radar normalization and anomaly peers.
Efficiency
ApprenticeBench API cost per task (NeoCognition)62$0.61
ApprenticeBench API cost per task (NeoCognition) published 2026-09-14 → · Claude Code — ApprenticeBench's published USD cost per task for each API-board model-harness-effort configuration on the 100-task accounts-payable job.
FrontierCode 1.1 Main cost per rollout (Cognition)developer's claim$2.12† self-reported by the developer
FrontierCode 1.1 Main cost per rollout (Cognition) v1.1 → · chisel — Cognition's published mean USD spend per rollout for each FrontierCode 1.1 Main model and reasoning effort.
Vals Index v2 cost per test (Vals AI)46$4.17
Vals Index v2 cost per test (Vals AI) v2 → · Published board — Vals AI's published USD cost per test for each model on the Vals Index v2.
FrontierCode 1.1 Extended cost per rollout (Cognition)developer's claim$1.79† self-reported by the developer
FrontierCode 1.1 Extended cost per rollout (Cognition) v1.1 → · chisel — Cognition's published mean USD spend per rollout for each FrontierCode 1.1 Extended model and reasoning effort.
Knowledge
Humanity's Last Exam (AA text-only)9647.9%
Humanity's Last Exam (AA text-only) published 2026-09-10 → · Published board — Tests expert-level knowledge on AA's text-only Humanity's Last Exam subset.
AA-Omniscience Index9326.5
AA-Omniscience Index published 2026-09-10 → · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
SimpleQA Verified (run by Epoch AI)8569.2%
SimpleQA Verified (run by Epoch AI) published 2026-09-16 → · Published board — Short fact-seeking questions answered without tools, testing whether a model knows a fact rather than guessing; Google DeepMind's cleaned version of OpenAI's SimpleQA, run by Epoch AI.
Legal Research Bench (Vals Index v2)3134.6%
Legal Research Bench (Vals Index v2) v2 → · Published board — Case and statute research with citation-backed answers.
Long-context
GDP.pdf (AA)8623.6%
GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.19381.7%
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA5315.0%
MLCR-AA published 2026-09-10 → · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.
Context Arena — MRCR v2 (8-needle)9696.0%
Context Arena — MRCR v2 (8-needle) 8-needle → · Published board — The model must find and reproduce the right one of eight near-identical earlier replies hidden in a long conversation, averaged over context lengths from 8k to 128k tokens.
Math
FrontierMath Tier 4 v2 (Epoch AI)5036.6%
FrontierMath Tier 4 v2 (Epoch AI) v2 → · Published board — The hardest, research-level tier of Epoch AI's unpublished FrontierMath problems, run by Epoch AI on its private v2 set.
FrontierMath Tiers 1–3 v2 (Epoch AI)6371.6%
FrontierMath Tiers 1–3 v2 (Epoch AI) v2 → · Published board — Unpublished, expert-written mathematics problems from undergraduate to research level with automatically checkable answers, run by Epoch AI on its private v2 set.
Reasoning
Chess Puzzles (Epoch AI)8847.0%
Chess Puzzles (Epoch AI) published 2026-09-18 → · Published board — Best-move selection on 100 novel chess positions generated programmatically by Epoch AI, each with a single Stockfish-verified best move; probes spatial reasoning and planning.
LiveBench 2026-06-256978.8
LiveBench 2026-06-25 → · Published board — A periodically refreshed suite of objectively graded tasks with separate category scores and an overall category mean.
Mystery Game Puzzles (Epoch AI)7637.0%
Mystery Game Puzzles (Epoch AI) published 2026-09-18 → · Published board — Best-move selection on 100 mid-game positions of a well-known game whose identity Epoch deliberately keeps undisclosed, generated programmatically like Chess Puzzles.
Science
CritPt (AA)8714.3%
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)9994.5%
GPQA Diamond (AA) published 2026-09-10 → · Published board — Tests graduate-level biology, physics and chemistry knowledge on the Diamond subset.
GPQA Diamond (Epoch AI run)9794.8%
GPQA Diamond (Epoch AI run) published 2026-09-18 → · Published board — Epoch AI's own inspect-ai runs of GPQA Diamond, the 198-question graduate-level science multiple-choice set.
Tool-use
AutomationBench-AA v1.0.69362.0%
AutomationBench-AA v1.0.6 → · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.
τ³-Banking (AA) v1.0.17332.8%
τ³-Banking (AA) v1.0.1 → · Published board — Tests banking support agents that retrieve policies and change account state through tools.
Excel Modeling Benchmark (Vals Index v2)7971.3%
Excel Modeling Benchmark (Vals Index v2) v2 → · Published board — Building and editing financial models in spreadsheets.
Vision
MMMU Pro (AA)9785.5%
MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.
Chartography 100-tasks7340.4%
Chartography 100-tasks → · Published board — Can a model read the charts professionals rely on — Kaplan-Meier curves, candlesticks, contour maps, Sankey diagrams, Bode plots, wind roses — from the image alone, to an expert-set precision?
GDP.pdf 100-tasks5723.8%
GDP.pdf 100-tasks → · Published board — Can a model answer real professional questions about the PDFs work runs on — manuals, wiring diagrams, filings, forms — so that every rubric criterion an expert wrote is met?
Furniture Assembly Benchmark (Epoch AI)1526.7%
Furniture Assembly Benchmark (Epoch AI) published 2026-09-26 → · Published board — Spatial-reasoning test by Epoch AI: given a photo of a partly or fully assembled IKEA product and its official manual, the model must say whether the build is correct and, if not, name the step with the mistake.
Unusual results
1 threshold-crossing signal flagged · 41 eligible benchmark families
How flags are calculated
Heuristic screen, not statistical significance: benchmark families are correlated and source uncertainty is unknown. Peer evidence needs ≥ 20 independently measured matched configurations from ≥ 10 distinct model families. A flag needs a directed population z-score of magnitude ≥ 1.5 and a gap of ≥ 1.5 from the leave-one-benchmark-family-out mean z in the same direction, over ≥ 5 other benchmark families.
- unusually strong Humanity's Last Exam (AA text-only) published 2026-09-10
Why
Observed: 0.47868 fractionPeer mean 0.15894 · peer sd 0.14559 · n 623 · families 450Directed z 2.196 · baseline z 0.661 · gap 1.535 · profile n 400.47868 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: Humanity's Last Exam (AA text-only) · published 2026-09-10 · Published boardExact value:0.478683966635774fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:b2331108-72ed-415a-82d1-188633875bbc:hle
Missing coverage · 271 benchmark versions
No result does not mean a zero, or that the model was never tested. Collection failures and disputed versions retain their distinct status.
Variants / reasoning settings
Artificial Analysis snapshot 2026-11-03 · Intelligence Index v5.0 (est. = estimated from v4, not measured) · Coding Index v4.x frozen 2026-10-27 · Data: Artificial Analysis · Data: Epoch AI (CC BY)
| Variant | AA Coding | AA Intelligence |
|---|---|---|
| Gemini 3.7 Flash (High) | 76.1 | 29.1est. |
| Gemini 3.7 Flash (Medium) | 71.5 | 29.8est. |
| Gemini 3.7 Flash (Low) | 71.0 | 26.0est. |
Token offers by platform · 3 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
3 offers within the active global filters, 1 more outside them; “price n/a” means the provider serves the model but publishes no direct token price we could collect — no other channel's price is shown in its place.
OpenRouter (2)
Prices via OpenRouter — what OpenRouter charges for each provider's endpoint, not the provider's own direct price. Source: openrouter.ai/google/gemini-3.7-flash/providers, collected 2026-11-03.
| globalgoogle-vertex/global | $0.750 raw in $/1M | $3.75 raw out $/1M | ||
| globalgoogle-vertex/us | $0.825 raw in $/1M | $4.13 raw out $/1M |
Google Vertex AI (1)
Direct prices from Google Vertex AI's own price list. Source: cloud.google.com/vertex-ai/generative-ai/pricing, collected 2026-11-03.
| Google Vertex AI | global | $0.750 raw in $/1M | $3.75 raw out $/1M |