Model comparison
Command R+ vs GLM-4.5
GLM-4.5 is the stronger model overall, scoring 42.0 to 32.4 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. Command R+ scores higher in 1 category and GLM-4.5 in 7 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 9.2.
- GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2.50 / $10 for Command R+.
- GLM-4.5 accepts more context: 131K tokens versus 128K.
Side by side
| Command R+ | GLM-4.5 | |
|---|---|---|
| Provider | Cohere | Z.ai (Zhipu) |
| Noometry Index | 32.4 | 42.0 |
| Released | 2024-08-30 | 2025-07-27 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 98K |
| Input $ / M tokens | $2.50 | $0.60 |
| Output $ / M tokens | $10 | $2.20 |
| Results tracked | 34 | 27 |
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Category by category
Coding GLM-4.5 leads
Command R+: 29.1 (#309), GLM-4.5: 41.4 (#125)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Coding | 1187 | 1434 |
| SWE-bench Verified (bash only) | — | 54.2% |
| WeirdML | — | 40.6% |
| BigCodeBench Instruct | 33.8% | — |
| LiveBench Coding | 19.1% | — |
| BigCodeBench Complete | 41.9% | — |
| ALE-Bench | — | 344.82 |
| AlgoTune | — | 1.52 |
| HumanEval+ | 56.7% | — |
| MBPP+ | 63.5% | — |
Reasoning GLM-4.5 leads
Command R+: 9.2 (#344), GLM-4.5: 28.6 (#100)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Hard Prompts | 1186 | 1429 |
| SimpleBench | 17.4% | — |
| Kagi LLM Benchmark | — | 57.9% |
| LiveBench Reasoning | 24.8% | — |
| DTBench | 54.9% | — |
| LiveBench Data Analysis | 38.1% | — |
| LMCA | 5% | — |
| Epoch Capabilities Index | 119.34 | — |
| LiveBench | 31.8% | — |
Math GLM-4.5 leads
Command R+: 28.9 (#242), GLM-4.5: 39.0 (#116)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Math | 1188 | 1427 |
| LiveBench Math | 21.3% | — |
Knowledge Too close to call
Command R+: 36.4 (#169), GLM-4.5: 35.9 (#179)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Expert | 1174 | 1433 |
| Humanity's Last Exam | — | 8.3% |
| Confabulations | — | 11.3% |
| Vectara Hallucination Rate | 6.9% | — |
| MMLU | 69.4% | — |
Multilingual GLM-4.5 leads
Command R+: 38.6 (#227), GLM-4.5: 52.8 (#77)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Non-English | 1216 | 1417 |
| LMArena Chinese | 1226 | 1465 |
| LMArena French | 1209 | 1418 |
| LMArena German | 1216 | 1407 |
| LMArena Japanese | 1166 | 1415 |
| LMArena Korean | 1138 | 1380 |
| LMArena Russian | 1227 | 1414 |
| LMArena Spanish | 1189 | 1454 |
Instruction Following GLM-4.5 leads
Command R+: 60.0 (#254), GLM-4.5: 74.1 (#104)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Instruction Following | 1197 | 1404 |
| LiveBench Instruction Following | 57.6% | — |
Long Context Too close to call
Command R+: 37.3 (#219), GLM-4.5: 38.2 (#201)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Longer Query | 1230 | 1412 |
| Fiction.LiveBench | — | 58.3% |
Writing & Preference GLM-4.5 leads
Command R+: 43.5 (#228), GLM-4.5: 57.5 (#127)
| Benchmark | Command R+ | GLM-4.5 |
|---|---|---|
| LMArena Text | 1229 | 1430 |
| LMArena Creative Writing | 1235 | 1395 |
| LMArena Multi-Turn | 1213 | 1415 |
| Short-Story Creative Writing | — | 73.4% |
| EQ-Bench Creative Writing | — | 1343 |
| LiveBench Language | 29.7% | — |
Frequently asked questions
Is Command R+ better than GLM-4.5?
GLM-4.5 is the stronger model overall, scoring 42.0 to 32.4 on the Noometry Index.
Which is cheaper, Command R+ or GLM-4.5?
GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Command R+ lists at $2.50 and $10.
Is Command R+ or GLM-4.5 better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 29.1 in the Noometry coding category.
Which has the bigger context window?
GLM-4.5 does, with 131K tokens against 128K.
How many benchmarks do Command R+ and GLM-4.5 share?
17 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and GLM-4.5 has 27.