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Command R (08-2024) vs GPT-5.6 Terra

Command R (08-2024) costs 20.0x less per output token than GPT-5.6 Terra ($0.60 vs $12.00 per million). Updated October 22, 2026; 25 benchmarks have a result for both.

Command R (08-2024)Cohere
Coding
No data
Overall
No data
Output $/M
$0.60
0
GPT-5.6 TerraOpenAI
Coding
63.9
Overall
68.1
Output $/M
$12.00
25
vs boards won of 25 shared

Command R (08-2024) or GPT-5.6 Terra: which to pick

Only GPT-5.6 Terra has a coding score, 63.9 on the Vibe Coding Index; Command R (08-2024) has none, so the two cannot be ranked on coding.

Pick Command R (08-2024) for output tokens 20.0x cheaper ($0.60 vs $12.00 per million).

Shared results
25
Command R (08-2024) only
0
GPT-5.6 Terra only
102
Like-for-like categories
5 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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
Command R (08-2024) not benchmarked, GPT-5.6 Terra 63.9 from 6 benchmarks.
Widest category
Reasoning, 48.7 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: expert: Command R (08-2024) 1173 against GPT-5.6 Terra 1496, 53.7 points apart on a 0 to 100 scale.
Output price
Command R (08-2024) $0.60 against GPT-5.6 Terra $12.00 per million output tokens, 20.0x apart.
Context window
Command R (08-2024) takes 128K tokens, GPT-5.6 Terra 1.05M.

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
CategoryCommand R (08-2024)BarsGPT-5.6 TerraTies
Coding02
Reasoning03
Math02
Knowledge04
General014
All shared boards025
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
LiveBench codingNot measured86.2%Only GPT-5.6 Terra measured
LMArena WebDevNot measured1522Only GPT-5.6 Terra measured
AA Coding IndexNot measured76.7Only GPT-5.6 Terra measured
LiveCodeBench (Vals AI)Not measured85.9%Only GPT-5.6 Terra measured
SWE-bench Verified (Vals AI)Not measured95.4%Only GPT-5.6 Terra measured
Terminal-Bench 4 (Vals AI)Not measured22.7%Only GPT-5.6 Terra measured
Vibe Code Bench (Vals AI)Not measured74.6%Only GPT-5.6 Terra measured
Code migration (Vals AI)Not measured47.8%Only GPT-5.6 Terra measured
ProgramBench (Vals AI)Not measured0.5%Only GPT-5.6 Terra measured
IOI (Vals AI)Not measured87.6%Only GPT-5.6 Terra measured
Terminal-Bench 2.1 (Vals AI)Not measured77.5%Only GPT-5.6 Terra measured
Vibe Code Bench 1-100 (Vals AI)Not measured14.8%Only GPT-5.6 Terra measured
SkillsBench (Vals AI)Not measured58.9%Only GPT-5.6 Terra measured
CyberBench (Vals AI)Not measured72.1%Only GPT-5.6 Terra measured
SciCodeNot measured55.0%Only GPT-5.6 Terra measured
Terminal-Bench Hard (Artificial Analysis run)Not measured62.9%Only GPT-5.6 Terra measured
FrontierCodeNot measured41.3%Only GPT-5.6 Terra measured
WeirdMLNot measured78.3%Only GPT-5.6 Terra measured
ALE-BenchNot measured1951.4Only GPT-5.6 Terra measured
LMArena Text: coding11871485GPT-5.6 Terra
LMArena Text: software and IT11971482GPT-5.6 Terra
LMArena WebDev: ReactNot measured1513Only GPT-5.6 Terra measured
LMArena WebDev: HTMLNot measured1526Only GPT-5.6 Terra measured
LMArena WebDev: from an imageNot measured1541Only GPT-5.6 Terra measured
SciCodeNot measured10.8%Only GPT-5.6 Terra measured
Neither model has a result on the other 14 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
AA Intelligence IndexNot measured42.1Only GPT-5.6 Terra measured
Epoch Capabilities IndexNot measured160.1Only GPT-5.6 Terra measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
Agentic work benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
AA Agentic IndexNot measured43.2Only GPT-5.6 Terra measured
Design Arena: agents building web appsNot measured1120Only GPT-5.6 Terra measured
Design Arena: agents building full-stack appsNot measured1061Only GPT-5.6 Terra measured
Design Arena: agents building mobile appsNot measured1111Only GPT-5.6 Terra measured
Design Arena: agents building Android appsNot measured1062Only GPT-5.6 Terra measured
Design Arena: agents building gamesNot measured1083Only GPT-5.6 Terra measured
Design Arena: HTML slidesNot measured1058Only GPT-5.6 Terra measured
Design Arena: PowerPoint slidesNot measured1105Only GPT-5.6 Terra measured
LiveBench researchNot measured60.4%Only GPT-5.6 Terra measured
LiveBench browserNot measured84.0%Only GPT-5.6 Terra measured
LiveBench long agenticNot measured48.4%Only GPT-5.6 Terra measured
SREBench (Vals AI)Not measured9.5%Only GPT-5.6 Terra measured
Finance Agent (Vals AI)Not measured54.4%Only GPT-5.6 Terra measured
Tax Agent Bench (Vals AI)Not measured30.0%Only GPT-5.6 Terra measured
Legal Research Bench (Vals AI)Not measured41.4%Only GPT-5.6 Terra measured
Excel Modeling Benchmark (Vals AI)Not measured66.2%Only GPT-5.6 Terra measured
Terminal-Bench-Science (Vals AI)Not measured10.0%Only GPT-5.6 Terra measured
τ²-Bench TelecomNot measured86.3%Only GPT-5.6 Terra measured
APEX-AgentsNot measured58.2%Only GPT-5.6 Terra measured
BALROGNot measured53.2%Only GPT-5.6 Terra measured
Vending-Bench 2Not measured$7,343Only GPT-5.6 Terra measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
GPQA DiamondNot measured90.9%Only GPT-5.6 Terra measured
LiveBench reasoningNot measured90.6%Only GPT-5.6 Terra measured
MMMU Pro (Vals AI)Not measured86.5%Only GPT-5.6 Terra measured
GPQA Diamond (Artificial Analysis run)Not measured92.5%Only GPT-5.6 Terra measured
Humanity's Last Exam (Artificial Analysis run)Not measured42.9%Only GPT-5.6 Terra measured
GPQA Diamond (Epoch AI run)Not measured93.3%Only GPT-5.6 Terra measured
ARC-AGINot measured96.5%Only GPT-5.6 Terra measured
ARC-AGI-2Not measured83.9%Only GPT-5.6 Terra measured
SimpleBenchNot measured48.9%Only GPT-5.6 Terra measured
Chess puzzlesNot measured47.0%Only GPT-5.6 Terra measured
Mystery game puzzlesNot measured35.0%Only GPT-5.6 Terra measured
LMArena Text: hard prompts11861469GPT-5.6 Terra
LMArena Text: expert11731496GPT-5.6 Terra
LMArena Text: hard prompts in English11941465GPT-5.6 Terra
LMArena Vision: diagramsNot measured1295Only GPT-5.6 Terra measured
LMArena Vision: homeworkNot measured1312Only GPT-5.6 Terra measured
Kagi LLM BenchmarkNot measured51.3%Only GPT-5.6 Terra measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
OTIS Mock AIMENot measured99.7%Only GPT-5.6 Terra measured
FrontierMath, tiers 1 to 3Not measured86.0%Only GPT-5.6 Terra measured
FrontierMath, tier 4Not measured70.7%Only GPT-5.6 Terra measured
ProofBenchNot measured74.0%Only GPT-5.6 Terra measured
LMArena Text: math11881465GPT-5.6 Terra
LMArena Text: mathematical work11981478GPT-5.6 Terra
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
MMLU ProNot measured86.7%Only GPT-5.6 Terra measured
LegalBench (Vals AI)Not measured85.1%Only GPT-5.6 Terra measured
CorpFin (Vals AI)Not measured65.3%Only GPT-5.6 Terra measured
TaxEval (Vals AI)Not measured76.2%Only GPT-5.6 Terra measured
MortgageTax (Vals AI)Not measured67.3%Only GPT-5.6 Terra measured
MedCode (Vals AI)Not measured43.4%Only GPT-5.6 Terra measured
SimpleQA VerifiedNot measured43.2%Only GPT-5.6 Terra measured
LMArena Text: science12521452GPT-5.6 Terra
LMArena Text: medicine and healthcare12381430GPT-5.6 Terra
LMArena Text: legal and government12681461GPT-5.6 Terra
LMArena Text: business and finance12151448GPT-5.6 Terra
FACTS Benchmark SuiteNot measured52.0%Only GPT-5.6 Terra measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
Design Arena: websitesNot measured1268Only GPT-5.6 Terra measured
Design Arena: UI componentsNot measured1256Only GPT-5.6 Terra measured
Design Arena: game devNot measured1229Only GPT-5.6 Terra measured
Design Arena: data vizNot measured1240Only GPT-5.6 Terra measured
Design Arena: 3DNot measured1134Only GPT-5.6 Terra measured
Design Arena: all code categoriesNot measured1241Only GPT-5.6 Terra measured
Design Arena: SVGNot measured1219Only GPT-5.6 Terra measured
Design Arena: ASCII artNot measured1177Only GPT-5.6 Terra measured
LiveBench designNot measured76.0%Only GPT-5.6 Terra measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
LiveBench data analysisNot measured79.3%Only GPT-5.6 Terra measured
Public Benefits Bench (Vals AI)Not measured62.4%Only GPT-5.6 Terra measured
SAGE (Vals AI)Not measured47.0%Only GPT-5.6 Terra measured
MedScribe (Vals AI)Not measured82.9%Only GPT-5.6 Terra measured
Vals Multimodal IndexNot measured65.1%Only GPT-5.6 Terra measured
IFBenchNot measured71.2%Only GPT-5.6 Terra measured
Long context reasoning (AA-LCR)Not measured83.0%Only GPT-5.6 Terra measured
DTBenchNot measured93.3%Only GPT-5.6 Terra measured
LMCANot measured54.9%Only GPT-5.6 Terra measured
Surface Evolver BenchNot measured83.8%Only GPT-5.6 Terra measured
Furniture assemblyNot measured54.2%Only GPT-5.6 Terra measured
LMArena Text12291448GPT-5.6 Terra
LMArena Text: instruction following11971456GPT-5.6 Terra
LMArena Text: creative writing12341413GPT-5.6 Terra
LMArena VisionNot measured1271Only GPT-5.6 Terra measured
LMArena Text: English12381449GPT-5.6 Terra
LMArena Text: non-English12161441GPT-5.6 Terra
LMArena Text: Chinese12271514GPT-5.6 Terra
LMArena Text: German12161460GPT-5.6 Terra
LMArena Text: Japanese11661454GPT-5.6 Terra
LMArena Text: Korean11621427GPT-5.6 Terra
LMArena Text: FrenchNot measured1466Only GPT-5.6 Terra measured
LMArena Text: SpanishNot measured1451Only GPT-5.6 Terra measured
LMArena Text: Russian12271452GPT-5.6 Terra
LMArena Text: PolishNot measured1446Only GPT-5.6 Terra measured
LMArena Text: multi-turn12131453GPT-5.6 Terra
LMArena Text: longer queries12301454GPT-5.6 Terra
LMArena Text: writing and language12411431GPT-5.6 Terra
LMArena Text: entertainment and media12231418GPT-5.6 Terra
LMArena Vision: EnglishNot measured1272Only GPT-5.6 Terra measured
LMArena Vision: ChineseNot measured1337Only GPT-5.6 Terra measured
LMArena Vision: reading textNot measured1278Only GPT-5.6 Terra measured
LMArena Vision: humorNot measured1236Only GPT-5.6 Terra measured
LMArena Vision: creative writingNot measured1248Only GPT-5.6 Terra measured
LMArena DocumentNot measured1472Only GPT-5.6 Terra 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 Command R (08-2024) and GPT-5.6 Terra
BenchmarkCommand R (08-2024)GPT-5.6 TerraLeader
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

Command R (08-2024)$0.0004Fits in one request
GPT-5.6 Terra$0.0080Fits in one request

Command R (08-2024) costs less

Repository review

50K input + 3K output tokens

Command R (08-2024)$0.0093Fits in one request
GPT-5.6 Terra$0.136Fits in one request

Command R (08-2024) costs less

Agent loop

200K input + 10K output tokens

Command R (08-2024)$0.036Exceeds the context window
GPT-5.6 Terra$0.520Fits in one request

Command R (08-2024) 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 Command R (08-2024) and GPT-5.6 Terra
SpecificationCohere Command R (08-2024)OpenAI GPT-5.6 Terra
MakerCohereOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 30, 2024July 9, 2026
Context window128K1.05M
Input $/Mtok$0.15$2.00
Output $/Mtok$0.60$12.00
Coding indexNot benchmarked63.9
Independent measurements behind it06
Cost per solved taskNot computable$0.42
SourceOpenRouter listingOpenRouter listing

Questions

Is Command R (08-2024) better than GPT-5.6 Terra for coding?

Only GPT-5.6 Terra has a coding score, 63.9 on the Vibe Coding Index; Command R (08-2024) has none, so the two cannot be ranked on coding. Pick Command R (08-2024) for output tokens 20.0x cheaper ($0.60 vs $12.00 per million).

Which is cheaper, Command R (08-2024) or GPT-5.6 Terra?

Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.6 Terra costs $2.00 and $12.00. Cost per solved task is known for GPT-5.6 Terra only.

Which has the bigger context window, Command R (08-2024) or GPT-5.6 Terra?

GPT-5.6 Terra, with 1.05M tokens against 128K.

How many benchmarks is the Command R (08-2024) vs GPT-5.6 Terra comparison based on?

25 benchmarks have a result for both models as of October 22, 2026. Command R (08-2024)'s coding index rests on 0 independent benchmarks and GPT-5.6 Terra's on 6. Where only one model has a result, the page says so instead of naming a winner.

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