Benchmark Heaven
Price & provider filters · adjusted costs
Global
Applies to price views & model offers; benchmark evidence stays unfiltered
← All models

Opus 4.7 (medium)

★ featured
Anthropic · 12 recorded token offers

Top 5 cheapest providers (Adjusted $/task)

Within the active global provider, residency and confidentiality filters.

#ProviderPlatformRaw input $/1MRaw output $/1MAdjusted $/task
1Google Vertex AIGoogle Vertex AI$5.00$25.00
2AnthropicAnthropic$5.00$25.00
3Claude Platform on AWSOpenRouter$5.00$25.00
4AzureOpenRouter$5.00$25.00
5GoogleOpenRouter$5.00$25.00

Benchmarks

Composite77.4
Mean-imputed base68.1
Dominance adjustment+9.4
Composite evidence1/5
AA Coding · unversioned snapshot 2026-09-10
AA Coding Agent · v1.4 · 2026-09-0946.7
AA Intelligence · unversioned snapshot 2026-09-10
DesignArena Frontend · unversioned snapshot 2026-09-10
DesignArena Full-Stack · unversioned snapshot 2026-09-10
Output speed (t/s)

MODEL EVIDENCE

Benchmark sheet

1 / 73 registered benchmark versions covered · 3 observations including existing index snapshots.

Compare this model ↗
Composite retains Coding Agent v1.4 · source 2026-09-09

The five Composite inputs remain unchanged. Its Coding Agent input is the median across complete harness results in the retained v1.4 snapshot from 2026-09-09. Artificial Analysis now publishes v1.5, with different components. Explore current v1.5 separately. Dated snapshot labels on other indices identify unversioned source captures, not a verified semantic version.

Profile signals

Insufficient evidence to evaluate · 0 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.

Protocol-compatible measured/vendor divergences

No verified protocol-compatible vendor/measured pair is available for this model; agreement cannot be assessed.

Coding

Coding: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
Artificial Analysis Coding Agent Index v1.4

Version 1.4

Claude Code

The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.

0.42389 fractionmeasuredobserved 2026-09-09artificialanalysis.ai
Evidence
Axis: Artificial Analysis Coding Agent Index v1.4 · 1.4 · Claude Code
Exact value: 0.423892771774363 fraction
Observed: 2026-09-09 · publication date: not recorded
Observation id: aa-coding:1.4:41
Artificial Analysis Coding Agent Index v1.4

Version 1.4

Cursor CLI

The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.

0.46655 fractionmeasuredobserved 2026-09-09artificialanalysis.ai
Evidence
Axis: Artificial Analysis Coding Agent Index v1.4 · 1.4 · Cursor CLI
Exact value: 0.466554082589455 fraction
Observed: 2026-09-09 · publication date: not recorded
Observation id: aa-coding:1.4:19
Artificial Analysis Coding Agent Index v1.4

Version 1.4

Opencode

The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.

0.51276 fractionmeasuredobserved 2026-09-09artificialanalysis.ai
Evidence
Axis: Artificial Analysis Coding Agent Index v1.4 · 1.4 · Opencode
Exact value: 0.5127556084440553 fraction
Observed: 2026-09-09 · publication date: not recorded
Observation id: aa-coding:1.4:23
Missing coverage · 76 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

VariantCoding · snapshot 2026-09-10Intelligence · snapshot 2026-09-10
Claude Opus 4.7 (Adaptive Reasoning, Max Effort)73.640.7
Claude Opus 4.7 (Non-reasoning, High Effort)30.9
Opus 4.7 (medium)

GitHub Copilot

Current usage-based billing · model token cost is converted to AI Credits at 1 credit = $0.01.

Input $5.00 / 1M
Cached input $0.500 / 1M
Cache write $6.25 / 1M
Output $25.00 / 1M
Status GA

Legacy annual Pro/Pro+ request billing only.

Multiplier 27.00×
Effective cost $1.080 / request

Legacy annual-plan multiplier.

Token offers by platform — Adjusted $/task

Adjusted costs are modeled USD per task: AA output tokens × OpenRouter usage I/O (Chutes global fallback). These are general usage and benchmark proxies for coding-agent work. Missing AA data assumes 1,000 output tokens/task; unknown cache hit assumes 0%; unmeasured additional cache writes assume 0 tokens. Click any underlined price for exact inputs, dates and assumptions. Raw list prices use the selected fixed input/output blend, in USD per million tokens.

12 offers within the active global filters; “—” means the catalog is active but no public token price is available.

Google Vertex AI (2)

Google Vertex AIglobal$5.00 raw in $/1M$25.00 raw out $/1M
Google Vertex AIeuEU$5.50 raw in $/1M$27.50 raw out $/1M

Anthropic (1)

Anthropicglobal$5.00 raw in $/1M$25.00 raw out $/1M

OpenRouter (8)

Claude Platform on AWSglobalclaude-on-aws$5.00 raw in $/1M$25.00 raw out $/1M
Azureglobalazure/global$5.00 raw in $/1M$25.00 raw out $/1M
Googleglobalgoogle-vertex/global$5.00 raw in $/1M$25.00 raw out $/1M
Amazon Bedrockglobalamazon-bedrock/global$5.00 raw in $/1M$25.00 raw out $/1M
Anthropicglobalanthropic$5.00 raw in $/1M$25.00 raw out $/1M
Googleglobalgoogle-vertex/us$5.50 raw in $/1M$27.50 raw out $/1M
Amazon Bedrockeuamazon-bedrock/eu-west-1EU$5.50 raw in $/1M$27.50 raw out $/1M
Googleeugoogle-vertex/europeEU$5.50 raw in $/1M$27.50 raw out $/1M

AWS Bedrock (1)

AWS Bedrockeu-central-1 (EU cross-region inference profile)EU$5.50 raw in $/1M$27.50 raw out $/1M
Benchmark Heaven — Model benchmarks & costs