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Claude Opus 4.8 vs Command A

Updated October 21, 2026. 51 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Claude Opus 4.8Anthropic
Coding
65.0
Overall
41.8
Output $/M
$25.00
50
Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
1
vs boards won of 51 shared

Decision reading

Only Claude Opus 4.8 has a coding score, 65.0 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 the benchmark that matters is IFBench, where it leads.

Shared results
51
Claude Opus 4.8 only
75
Command A only
9
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 4.8 65.0 from 6 benchmarks, Command A not benchmarked.
Widest category
Coding, 41.9 points apart on average over 8 shared benchmarks.
Widest single gap
SWE-bench Verified (Vals AI): Claude Opus 4.8 88.6% against Command A 7.8%, 80.8 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against Command A $10.00 per million output tokens, 2.5x apart.
Context window
Claude Opus 4.8 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 4.8BarsCommand ATies
Coding80
Intelligence10
Agentic work30
Reasoning60
Math20
Knowledge90
General211
All shared boards501
CodingLike-for-likeSix of these boards feed the Vibe Coding Index80
Coding benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
LiveBench coding77.3%Not measuredOnly Claude Opus 4.8 measured
LMArena WebDev1556Not measuredOnly Claude Opus 4.8 measured
AA Coding Index74.327.8Claude Opus 4.8
LiveCodeBench (Vals AI)87.8%35.1%Claude Opus 4.8
SWE-bench Verified (Vals AI)88.6%7.8%Claude Opus 4.8
Terminal-Bench 4 (Vals AI)23.2%Not measuredOnly Claude Opus 4.8 measured
Vibe Code Bench (Vals AI)82.7%Not measuredOnly Claude Opus 4.8 measured
Code migration (Vals AI)47.3%Not measuredOnly Claude Opus 4.8 measured
ProgramBench (Vals AI)1.0%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench 2.1 (Vals AI)71.9%17.6%Claude Opus 4.8
SkillsBench (Vals AI)59.2%Not measuredOnly Claude Opus 4.8 measured
LiveCodeBench (Artificial Analysis run)Not measured28.7%Only Command A measured
SciCode54.4%38.5%Claude Opus 4.8
Terminal-Bench Hard (Artificial Analysis run)58.3%25.0%Claude Opus 4.8
FrontierCode46.5%Not measuredOnly Claude Opus 4.8 measured
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: coding14901330Claude Opus 4.8
LMArena Text: software and IT14881336Claude Opus 4.8
LMArena WebDev: React1557Not measuredOnly Claude Opus 4.8 measured
LMArena WebDev: HTML1543Not measuredOnly Claude Opus 4.8 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 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
AA Intelligence Index41.813.1Claude Opus 4.8
Epoch Capabilities Index159.0Not measuredOnly Claude Opus 4.8 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index30
Agentic work benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
AA Agentic Index41.91.0Claude Opus 4.8
Design Arena: agents building web apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building full-stack apps1249Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building mobile apps1223Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Android apps1238Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Godot games1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building games1238Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides1221Not measuredOnly Claude Opus 4.8 measured
Design Arena: PowerPoint slides1227Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%Not measuredOnly Claude Opus 4.8 measured
LiveBench browser96.0%Not measuredOnly Claude Opus 4.8 measured
LiveBench long agentic48.3%Not measuredOnly Claude Opus 4.8 measured
Finance Agent (Vals AI)53.9%9.0%Claude Opus 4.8
Tax Agent Bench (Vals AI)30.0%Not measuredOnly Claude Opus 4.8 measured
Legal Research Bench (Vals AI)43.8%Not measuredOnly Claude Opus 4.8 measured
Excel Modeling Benchmark (Vals AI)69.4%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly Claude Opus 4.8 measured
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%80.7%Claude Opus 4.8
APEX-Agents48.9%Not measuredOnly Claude Opus 4.8 measured
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787Not measuredOnly Claude Opus 4.8 measured
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 13 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
GPQA Diamond92.4%48.5%Claude Opus 4.8
LiveBench reasoning89.2%Not measuredOnly Claude Opus 4.8 measured
MMMU Pro (Vals AI)86.6%Not measuredOnly Claude Opus 4.8 measured
GPQA Diamond (Artificial Analysis run)92.0%76.1%Claude Opus 4.8
Humanity's Last Exam (Artificial Analysis run)48.7%12.0%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%Not measuredOnly Claude Opus 4.8 measured
ARC-AGI92.5%Not measuredOnly Claude Opus 4.8 measured
ARC-AGI-272.1%Not measuredOnly Claude Opus 4.8 measured
SimpleBench64.8%Not measuredOnly Claude Opus 4.8 measured
Chess puzzles52.0%Not measuredOnly Claude Opus 4.8 measured
Mystery game puzzles36.0%Not measuredOnly Claude Opus 4.8 measured
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821326Claude Opus 4.8
LMArena Text: expert15031296Claude Opus 4.8
LMArena Text: hard prompts in English14871335Claude Opus 4.8
LMArena Vision: diagrams1315Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
AIMENot measured13.3%Only Command A measured
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 AIME98.3%Not measuredOnly Claude Opus 4.8 measured
FrontierMath, tiers 1 to 380.0%Not measuredOnly Claude Opus 4.8 measured
FrontierMath, tier 456.1%Not measuredOnly Claude Opus 4.8 measured
ProofBench69.0%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: math14861300Claude Opus 4.8
LMArena Text: mathematical work14971312Claude Opus 4.8
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
MMLU Pro89.6%69.2%Claude Opus 4.8
LegalBench (Vals AI)83.6%79.7%Claude Opus 4.8
CaseLaw (Vals AI)Not measured64.5%Only Command A measured
CorpFin (Vals AI)66.7%46.0%Claude Opus 4.8
TaxEval (Vals AI)75.6%61.4%Claude Opus 4.8
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedQA (Vals AI)Not measured80.5%Only Command A measured
MedCode (Vals AI)53.2%19.7%Claude Opus 4.8
MMLU Pro (Artificial Analysis run)Not measured71.2%Only Command A measured
SimpleQA Verified53.0%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: science14771339Claude Opus 4.8
LMArena Text: medicine and healthcare14641334Claude Opus 4.8
LMArena Text: legal and government14771348Claude Opus 4.8
LMArena Text: business and finance14581315Claude Opus 4.8
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
Design Arena: websites1259Not measuredOnly Claude Opus 4.8 measured
Design Arena: UI components1257Not measuredOnly Claude Opus 4.8 measured
Design Arena: game dev1264Not measuredOnly Claude Opus 4.8 measured
Design Arena: data viz1239Not measuredOnly Claude Opus 4.8 measured
Design Arena: 3D1223Not measuredOnly Claude Opus 4.8 measured
Design Arena: all code categories1255Not measuredOnly Claude Opus 4.8 measured
Design Arena: SVG1194Not measuredOnly Claude Opus 4.8 measured
Design Arena: ASCII art1276Not measuredOnly Claude Opus 4.8 measured
LiveBench design78.8%Not measuredOnly Claude Opus 4.8 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index211
General benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command ALeader
LiveBench data analysis66.0%Not measuredOnly Claude Opus 4.8 measured
Public Benefits Bench (Vals AI)68.1%Not measuredOnly Claude Opus 4.8 measured
SAGE (Vals AI)54.8%Not measuredOnly Claude Opus 4.8 measured
MedScribe (Vals AI)85.8%55.7%Claude Opus 4.8
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%73.9%Command A
Long context reasoning (AA-LCR)77.7%52.7%Claude Opus 4.8
DTBench94.9%61.3%Claude Opus 4.8
LMCA57.5%10.3%Claude Opus 4.8
Surface Evolver Bench87.5%Not measuredOnly Claude Opus 4.8 measured
Furniture assembly42.5%Not measuredOnly Claude Opus 4.8 measured
LMArena Text14611331Claude Opus 4.8
LMArena Text: instruction following14761309Claude Opus 4.8
LMArena Text: creative writing14541319Claude Opus 4.8
LMArena Vision1294Not measuredOnly Claude Opus 4.8 measured
LMArena Text: English14681344Claude Opus 4.8
LMArena Text: non-English14501313Claude Opus 4.8
LMArena Text: Chinese15061327Claude Opus 4.8
LMArena Text: German14721342Claude Opus 4.8
LMArena Text: Japanese14421285Claude Opus 4.8
LMArena Text: Korean14311285Claude Opus 4.8
LMArena Text: French14811351Claude Opus 4.8
LMArena Text: Spanish14651347Claude Opus 4.8
LMArena Text: Russian14741314Claude Opus 4.8
LMArena Text: Polish14591324Claude Opus 4.8
LMArena Text: multi-turn14761338Claude Opus 4.8
LMArena Text: longer queries14831334Claude Opus 4.8
LMArena Text: writing and language14611328Claude Opus 4.8
LMArena Text: entertainment and media14401306Claude Opus 4.8
LMArena Vision: English1293Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: Chinese1346Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: reading text1303Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: humor1282Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: creative writing1301Not measuredOnly Claude Opus 4.8 measured
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and Command A
BenchmarkClaude Opus 4.8Command 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 4.8$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 4.8$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 4.8$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 4.8 and Command A
SpecificationAnthropic Claude Opus 4.8Cohere Command A
MakerAnthropicCohere
WeightsNo public weights listedOpen weights
ReleasedMay 27, 2026March 13, 2025
Context window1M256K
Input $/Mtok$5.00$2.50
Output $/Mtok$25.00$10.00
Coding index65.0Not benchmarked
Independent measurements behind it61
Cost per solved task$2.17$2.69
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than Command A for coding?

Only Claude Opus 4.8 has a coding score, 65.0 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 the benchmark that matters is IFBench, where it leads.

Which is cheaper, Claude Opus 4.8 or Command A?

Claude Opus 4.8 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 4.8 costs $2.17 and Command A $2.69.

Which has the bigger context window, Claude Opus 4.8 or Command A?

Claude Opus 4.8, with 1M tokens against 256K.

How many benchmarks is the Claude Opus 4.8 vs Command A comparison based on?

51 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.8's coding index rests on 6 independent benchmarks and Command A's on 1. Where only one model has a result, the page says so instead of naming a winner.

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