Model comparison
Command A vs GLM-4.6
GLM-4.6 is the stronger model overall, scoring 40.9 to 35.9 on the Noometry Index.
Last verified . 21 shared benchmarks.
CohereSummary
- They share 21 benchmarks with published results for both. Command A scores higher in 1 category and GLM-4.6 in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.3 to 47.8.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for Command A and 47.4% for GLM-4.6.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2.50 / $10 for Command A.
- Command A accepts more context: 256K tokens versus 205K.
Side by side
| Command A | GLM-4.6 | |
|---|---|---|
| Provider | Cohere | Z.ai (Zhipu) |
| Noometry Index | 35.9 | 40.9 |
| Released | 2025-03-13 | 2025-09-30 |
| Weights | Open | Open |
| Context window | 256K | 205K |
| Max output | 8K | 131K |
| Input $ / M tokens | $2.50 | $0.60 |
| Output $ / M tokens | $10 | $2.20 |
| Results tracked | 24 | 29 |
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Category by category
Coding GLM-4.6 leads
Command A: 26.8 (#317), GLM-4.6: 39.9 (#137)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| LMArena Coding | 1331 | 1449 |
| SWE-bench Verified (bash only) | — | 55.4% |
| Aider Polyglot | 12% | — |
| LMArena WebDev | — | 1339 |
| SciCode | — | 38.4% |
| ALE-Bench | — | 340.82 |
Agentic & Tool Use Command A leads
Command A: 35.7 (#36), GLM-4.6: 32.1 (#60)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | 72.4% |
| Terminal-Bench | — | 24.5% |
Reasoning GLM-4.6 leads
Command A: 17.7 (#276), GLM-4.6: 23.1 (#168)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 47.4% |
| LMArena Hard Prompts | 1326 | 1440 |
| CritPt | — | 1.1% |
| DTBench | 61.3% | — |
| LMCA | 10.3% | — |
Math GLM-4.6 leads
Command A: 33.5 (#172), GLM-4.6: 36.4 (#115)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| LMArena Math | 1300 | 1431 |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GLM-4.6 leads
Command A: 36.5 (#157), GLM-4.6: 39.6 (#118)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 9.5% |
| LMArena Expert | 1295 | 1432 |
Multilingual GLM-4.6 leads
Command A: 45.5 (#166), GLM-4.6: 53.6 (#62)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 1313 | 1426 |
| LMArena Chinese | 1327 | 1500 |
| LMArena French | 1352 | 1459 |
| LMArena German | 1341 | 1447 |
| LMArena Japanese | 1283 | 1394 |
| LMArena Korean | 1285 | 1401 |
| LMArena Russian | 1314 | 1418 |
| LMArena Spanish | 1346 | 1436 |
Instruction Following GLM-4.6 leads
Command A: 69.3 (#172), GLM-4.6: 74.5 (#93)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1309 | 1410 |
Long Context GLM-4.6 leads
Command A: 40.6 (#147), GLM-4.6: 43.4 (#91)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | 1334 | 1423 |
Writing & Preference GLM-4.6 leads
Command A: 47.8 (#204), GLM-4.6: 61.3 (#86)
| Benchmark | Command A | GLM-4.6 |
|---|---|---|
| LMArena Text | 1331 | 1440 |
| LMArena Creative Writing | 1319 | 1411 |
| EQ-Bench Creative Writing | 1145 | 1411 |
| LMArena Multi-Turn | 1338 | 1427 |
Frequently asked questions
Is Command A better than GLM-4.6?
GLM-4.6 is the stronger model overall, scoring 40.9 to 35.9 on the Noometry Index.
Which is cheaper, Command A or GLM-4.6?
GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Command A lists at $2.50 and $10.
Is Command A or GLM-4.6 better for coding?
GLM-4.6 scores higher on coding benchmarks: 39.9 versus 26.8 in the Noometry coding category.
Which has the bigger context window?
Command A does, with 256K tokens against 205K.
How many benchmarks do Command A and GLM-4.6 share?
21 benchmarks have published results for both models. Command A has 24 scored results on Noometry and GLM-4.6 has 29.