Model comparison
Command R vs GPT-5.6 Terra
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 31.4 on the Noometry Index. Command R costs 17× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
CohereSummary
- They share 19 benchmarks with published results for both. Command R scores higher in 0 categories and GPT-5.6 Terra in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 28.0.
- The biggest single-benchmark swing is DTBench: 46.4% for Command R and 93.3% for GPT-5.6 Terra.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 128K.
- Command R has downloadable open weights; the other is API-only.
Side by side
| Command R | GPT-5.6 Terra | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 31.4 | 59.2 |
| Released | 2024-08-30 | 2026-07-09 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 128K |
| Input $ / M tokens | $0.15 | $2 |
| Output $ / M tokens | $0.60 | $12 |
| Results tracked | 29 | 52 |
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Category by category
Coding GPT-5.6 Terra leads
Command R: 29.3 (#306), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Coding | 1169 | 1484 |
| DeepSWE | — | 69.6% |
| FrontierCode | — | 41.3% |
| CursorBench | — | 41.3% |
| LMArena WebDev | — | 1522 |
| SciCode | — | 55% |
| WeirdML | — | 78.3% |
| BigCodeBench Instruct | 37.1% | — |
| LiveBench Coding | 17.9% | — |
| BigCodeBench Complete | 45.2% | — |
| ALE-Bench | — | 1,951 |
Agentic & Tool Use Not comparable
Command R: —, GPT-5.6 Terra: 40.1 (#25)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| APEX-Agents | — | 58.2% |
| BALROG | — | 53.2% |
| GDP.pdf | — | 24.7% |
| Vending-Bench 2 | — | 7,343 |
Reasoning GPT-5.6 Terra leads
Command R: 13.8 (#331), GPT-5.6 Terra: 60.7 (#21)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1468 |
| DTBench | 46.4% | 93.3% |
| LMCA | 9.2% | 55% |
| ARC-AGI-2 | — | 83.9% |
| SimpleBench | — | 48.9% |
| Kagi LLM Benchmark | — | 51.3% |
| NYT Connections (extended) | — | 78.4% |
| ARC-AGI-1 | — | 96.5% |
| CritPt | — | 30% |
| Chess Puzzles | — | 54% |
| LiveBench Reasoning | 21.9% | — |
| Mystery Game Puzzles | — | 35% |
| LiveBench Data Analysis | 33.3% | — |
| Surface Evolver Bench | — | 83.8% |
| Epoch Capabilities Index | — | 159.62 |
| LiveBench | 27.5% | — |
Math GPT-5.6 Terra leads
Command R: 28.0 (#246), GPT-5.6 Terra: 81.6 (#12)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Math | 1155 | 1466 |
| FrontierMath (Tiers 1-3) | — | 86% |
| FrontierMath Tier 4 | — | 70.7% |
| OTIS Mock AIME 2024-2025 | — | 99.7% |
| ProofBench | — | 74% |
| LiveBench Math | 19.4% | — |
Knowledge GPT-5.6 Terra leads
Command R: 31.0 (#221), GPT-5.6 Terra: 61.2 (#30)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Expert | 1138 | 1492 |
| GPQA Diamond | — | 93.3% |
| SimpleQA Verified | — | 43.2% |
| MMLU | 65.2% | — |
Multimodal Not comparable
Command R: —, GPT-5.6 Terra: 47.3 (#11)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | — | 1271 |
| Blueprint-Bench 2 | — | 30.8% |
| Furniture Assembly | — | 54.2% |
| LMArena Document | — | 1472 |
Multilingual GPT-5.6 Terra leads
Command R: 35.7 (#245), GPT-5.6 Terra: 54.4 (#44)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1174 | 1439 |
| LMArena Chinese | 1182 | 1513 |
| LMArena French | 1162 | 1471 |
| LMArena German | 1176 | 1460 |
| LMArena Japanese | 1143 | 1457 |
| LMArena Korean | 1163 | 1425 |
| LMArena Russian | 1174 | 1450 |
| LMArena Spanish | 1151 | 1448 |
Instruction Following GPT-5.6 Terra leads
Command R: 58.1 (#261), GPT-5.6 Terra: 76.4 (#40)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1167 | 1454 |
| LiveBench Instruction Following | 55.6% | — |
Long Context GPT-5.6 Terra leads
Command R: 36.3 (#231), GPT-5.6 Terra: 44.4 (#68)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1198 | 1451 |
Writing & Preference GPT-5.6 Terra leads
Command R: 38.2 (#254), GPT-5.6 Terra: 70.2 (#23)
| Benchmark | Command R | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1187 | 1447 |
| LMArena Creative Writing | 1170 | 1410 |
| LMArena Multi-Turn | 1163 | 1449 |
| EQ-Bench Creative Writing | — | 1855 |
| EQ-Bench 4 | — | 1234 |
| LiveBench Language | 16.7% | — |
Frequently asked questions
Is Command R better than GPT-5.6 Terra?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 31.4 on the Noometry Index. Command R costs 17× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.
Which is cheaper, Command R or GPT-5.6 Terra?
Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.6 Terra lists at $2 and $12.
Is Command R or GPT-5.6 Terra better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 29.3 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 128K.
How many benchmarks do Command R and GPT-5.6 Terra share?
19 benchmarks have published results for both models. Command R has 29 scored results on Noometry and GPT-5.6 Terra has 52.