Enter opens the highlighted result. Esc closes.

Claude Opus 4.7 vs Command A

Updated October 21, 2026. 52 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Claude Opus 4.7Anthropic
Coding
67.5
Overall
40.7
Output $/M
$25.00
51
Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
1
vs boards won of 52 shared

Decision reading

Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Command A has none, so the two cannot be ranked on coding.

Command A has the edge where output tokens cost 2.5x less, and where a solved task costs $2.69 against $2.95.

Shared results
52
Claude Opus 4.7 only
49
Command A only
8
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Claude Opus 4.7 67.5 from 4 benchmarks, Command A not benchmarked.
Widest category
Math, 49.6 points apart on average over 3 shared benchmarks.
Widest single gap
AIME: Claude Opus 4.7 96.3% against Command A 13.3%, 82.9 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.7 $25.00 against Command A $10.00 per million output tokens, 2.5x apart.
Context window
Claude Opus 4.7 takes 1M tokens, Command A 256K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryClaude Opus 4.7BarsCommand ATies
Coding70
Intelligence10
Agentic work30
Reasoning60
Math30
Knowledge100
General211
All shared boards511
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
LMArena WebDev1558Not measuredOnly Claude Opus 4.7 measured
AA Coding Index73.627.8Claude Opus 4.7
LiveCodeBench (Vals AI)85.1%35.1%Claude Opus 4.7
SWE-bench Verified (Vals AI)82.0%7.8%Claude Opus 4.7
Vibe Code Bench (Vals AI)71.0%Not measuredOnly Claude Opus 4.7 measured
Code migration (Vals AI)43.9%Not measuredOnly Claude Opus 4.7 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Opus 4.7 measured
Terminal-Bench 2.1 (Vals AI)68.5%17.6%Claude Opus 4.7
LiveCodeBench (Artificial Analysis run)Not measured28.7%Only Command A measured
SciCodeNot measured38.5%Only Command A measured
Terminal-Bench Hard (Artificial Analysis run)54.5%25.0%Claude Opus 4.7
Terminal-Bench80.2%Not measuredOnly Claude Opus 4.7 measured
FrontierCode38.5%Not measuredOnly Claude Opus 4.7 measured
GSO-Bench44.1%Not measuredOnly Claude Opus 4.7 measured
WeirdML76.4%Not measuredOnly Claude Opus 4.7 measured
MirrorCode31.1%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: coding15191330Claude Opus 4.7
LMArena Text: software and IT15161336Claude Opus 4.7
LMArena WebDev: React1560Not measuredOnly Claude Opus 4.7 measured
LMArena WebDev: HTML1554Not measuredOnly Claude Opus 4.7 measured
LMArena WebDev: from an image1577Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
AA Intelligence Index40.713.1Claude Opus 4.7
Epoch Capabilities Index156.8Not measuredOnly Claude Opus 4.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index30
Agentic work benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
AA Agentic Index38.61.0Claude Opus 4.7
Finance Agent (Vals AI)51.5%9.0%Claude Opus 4.7
Tax Agent Bench (Vals AI)23.7%Not measuredOnly Claude Opus 4.7 measured
Legal Research Bench (Vals AI)38.5%Not measuredOnly Claude Opus 4.7 measured
Excel Modeling Benchmark (Vals AI)63.7%Not measuredOnly Claude Opus 4.7 measured
τ²-Bench Telecom88.6%80.7%Claude Opus 4.7
APEX-Agents49.2%Not measuredOnly Claude Opus 4.7 measured
OSWorld 2.018.2%Not measuredOnly Claude Opus 4.7 measured
PostTrainBench28.6%Not measuredOnly Claude Opus 4.7 measured
Vending-Bench 2$10,937Not measuredOnly Claude Opus 4.7 measured
LMArena Search1230Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
GPQA Diamond90.2%48.5%Claude Opus 4.7
MMMU Pro (Vals AI)85.5%Not measuredOnly Claude Opus 4.7 measured
GPQA Diamond (Artificial Analysis run)91.4%76.1%Claude Opus 4.7
Humanity's Last Exam (Artificial Analysis run)42.3%12.0%Claude Opus 4.7
GPQA Diamond (Epoch AI run)90.2%Not measuredOnly Claude Opus 4.7 measured
ARC-AGI93.5%Not measuredOnly Claude Opus 4.7 measured
ARC-AGI-275.8%Not measuredOnly Claude Opus 4.7 measured
SimpleBench61.7%Not measuredOnly Claude Opus 4.7 measured
Chess puzzles41.0%Not measuredOnly Claude Opus 4.7 measured
Mystery game puzzles28.0%Not measuredOnly Claude Opus 4.7 measured
EBR-bench19.0%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: hard prompts15061326Claude Opus 4.7
LMArena Text: expert15211296Claude Opus 4.7
LMArena Text: hard prompts in English15081335Claude Opus 4.7
LMArena Vision: diagrams1336Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
AIME96.3%13.3%Claude Opus 4.7
MATH 500 (Vals AI)Not measured76.2%Only Command A measured
MGSM (Vals AI)Not measured85.7%Only Command A measured
AA Math IndexNot measured13.0Only Command A measured
AIME 2025 (Artificial Analysis run)Not measured13.0%Only Command A measured
OTIS Mock AIME97.8%Not measuredOnly Claude Opus 4.7 measured
FrontierMath, tiers 1 to 370.2%Not measuredOnly Claude Opus 4.7 measured
FrontierMath, tier 431.7%Not measuredOnly Claude Opus 4.7 measured
ProofBench54.0%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: math14981300Claude Opus 4.7
LMArena Text: mathematical work15091312Claude Opus 4.7
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index100
Knowledge benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
MMLU Pro89.9%69.2%Claude Opus 4.7
LegalBench (Vals AI)85.3%79.7%Claude Opus 4.7
CaseLaw (Vals AI)68.4%64.5%Claude Opus 4.7
CorpFin (Vals AI)66.1%46.0%Claude Opus 4.7
TaxEval (Vals AI)75.3%61.4%Claude Opus 4.7
MortgageTax (Vals AI)70.3%Not measuredOnly Claude Opus 4.7 measured
MedQA (Vals AI)Not measured80.5%Only Command A measured
MedCode (Vals AI)54.9%19.7%Claude Opus 4.7
MMLU Pro (Artificial Analysis run)Not measured71.2%Only Command A measured
SimpleQA Verified51.7%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: science15081339Claude Opus 4.7
LMArena Text: medicine and healthcare14951334Claude Opus 4.7
LMArena Text: legal and government15041348Claude Opus 4.7
LMArena Text: business and finance14901315Claude Opus 4.7
Neither model has a result on the other 3 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index211
General benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
SAGE (Vals AI)56.1%Not measuredOnly Claude Opus 4.7 measured
MedScribe (Vals AI)83.0%55.7%Claude Opus 4.7
Vals Multimodal Index67.4%Not measuredOnly Claude Opus 4.7 measured
IFBench58.6%73.9%Command A
Long context reasoning (AA-LCR)78.7%52.7%Claude Opus 4.7
DTBench94.7%61.3%Claude Opus 4.7
LMCA52.2%10.3%Claude Opus 4.7
Furniture assembly33.3%Not measuredOnly Claude Opus 4.7 measured
ExploitBench26.5%Not measuredOnly Claude Opus 4.7 measured
LMArena Text14901331Claude Opus 4.7
LMArena Text: instruction following14981309Claude Opus 4.7
LMArena Text: creative writing14861319Claude Opus 4.7
LMArena Vision1317Not measuredOnly Claude Opus 4.7 measured
LMArena Text: English14961344Claude Opus 4.7
LMArena Text: non-English14801313Claude Opus 4.7
LMArena Text: Chinese15311327Claude Opus 4.7
LMArena Text: German14951342Claude Opus 4.7
LMArena Text: Japanese14741285Claude Opus 4.7
LMArena Text: Korean14641285Claude Opus 4.7
LMArena Text: French15031351Claude Opus 4.7
LMArena Text: Spanish14941347Claude Opus 4.7
LMArena Text: Russian14941314Claude Opus 4.7
LMArena Text: Polish14891324Claude Opus 4.7
LMArena Text: multi-turn15051338Claude Opus 4.7
LMArena Text: longer queries15051334Claude Opus 4.7
LMArena Text: writing and language14921328Claude Opus 4.7
LMArena Text: entertainment and media14741306Claude Opus 4.7
LMArena Vision: English1322Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: Chinese1371Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: reading text1327Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: humor1309Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: recognizing things1278Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: creative writing1326Not measuredOnly Claude Opus 4.7 measured
LMArena Document1495Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.7 and Command A
BenchmarkClaude Opus 4.7Command ALeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Claude Opus 4.7$0.018Fits in one request
Command A$0.0075Fits in one request

Command A costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.7$0.325Fits in one request
Command A$0.155Fits in one request

Command A costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.7$1.25Fits in one request
Command A$0.600Fits in one request

Command A costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Claude Opus 4.7 and Command A
SpecificationAnthropic Claude Opus 4.7Cohere Command A
MakerAnthropicCohere
WeightsNo public weights listedOpen weights
ReleasedApril 16, 2026March 13, 2025
Context window1M256K
Input $/Mtok$5.00$2.50
Output $/Mtok$25.00$10.00
Coding index67.5Not benchmarked
Independent measurements behind it41
Cost per solved task$2.95$2.69
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.7 better than Command A for coding?

Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Command A has none, so the two cannot be ranked on coding. Command A has the edge where output tokens cost 2.5x less, and where a solved task costs $2.69 against $2.95.

Which is cheaper, Claude Opus 4.7 or Command A?

Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; Command A costs $2.50 and $10.00. Per solved SWE-bench Verified task, Claude Opus 4.7 costs $2.95 and Command A $2.69.

Which has the bigger context window, Claude Opus 4.7 or Command A?

Claude Opus 4.7, with 1M tokens against 256K.

How many benchmarks is the Claude Opus 4.7 vs Command A comparison based on?

52 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.7's coding index rests on 4 independent benchmarks and Command A's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next