Model comparison
GLM-5.1 vs Pixtral Large
GLM-5.1 is the stronger model overall, scoring 47.8 to 32.2 on the Noometry Index.
Last verified . 1 shared benchmarks.
Mistral AISummary
- They share 1 benchmark with published results for both. GLM-5.1 scores higher in 2 categories and Pixtral Large in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5.1 leads 66.9 to 32.9.
- GLM-5.1 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2 / $6 for Pixtral Large.
- GLM-5.1 accepts more context: 200K tokens versus 128K.
Side by side
| GLM-5.1 | Pixtral Large | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 47.8 | 32.2 |
| Released | 2026-04-07 | 2024-11-01 |
| Weights | Open | Open |
| Context window | 200K | 128K |
| Max output | 131K | 128K |
| Input $ / M tokens | $1.40 | $2 |
| Output $ / M tokens | $4.40 | $6 |
| Results tracked | 41 | 3 |
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Category by category
Coding Not comparable
GLM-5.1: 48.7 (#55), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| SWE-bench Verified | 74.2% | — |
| LMArena WebDev | 1508 | — |
| SciCode | 43.8% | — |
| WeirdML | 57.1% | — |
| LMArena Coding | 1485 | — |
| ALE-Bench | 887.1 | — |
Agentic & Tool Use Not comparable
GLM-5.1: 24.9 (#113), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| APEX-Agents | 40.9% | — |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 5,634 | — |
Reasoning GLM-5.1 leads
GLM-5.1: 39.1 (#60), Pixtral Large: 21.7 (#218)
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| SimpleBench | 55.1% | — |
| NYT Connections (extended) | 77.7% | — |
| CritPt | 4.6% | — |
| Chess Puzzles | 19% | — |
| EnigmaEval | — | 0.8% |
| Thematic Generalization | 69.8% | — |
| LMArena Hard Prompts | 1472 | — |
| Epoch Capabilities Index | 149.84 | — |
Math Not comparable
GLM-5.1: 49.7 (#60), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| OTIS Mock AIME 2024-2025 | 93.3% | — |
| ProofBench | 22.2% | — |
| LMArena Math | 1473 | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge Not comparable
GLM-5.1: 54.9 (#50), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| GPQA Diamond | 89.9% | — |
| SimpleQA Verified | 34% | — |
| LMArena Expert | 1476 | — |
Multimodal Not comparable
GLM-5.1: —, Pixtral Large: 30.6 (#111)
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |
Multilingual Not comparable
GLM-5.1: 55.0 (#36), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1447 | — |
| LMArena Chinese | 1515 | — |
| LMArena French | 1474 | — |
| LMArena German | 1465 | — |
| LMArena Japanese | 1434 | — |
| LMArena Korean | 1418 | — |
| LMArena Russian | 1454 | — |
| LMArena Spanish | 1469 | — |
Instruction Following Not comparable
GLM-5.1: 76.3 (#42), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| LMArena Instruction Following | 1451 | — |
Long Context Not comparable
GLM-5.1: 44.9 (#53), Pixtral Large: —
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| LMArena Longer Query | 1466 | — |
Writing & Preference GLM-5.1 leads
GLM-5.1: 66.9 (#31), Pixtral Large: 32.9 (#278)
| Benchmark | GLM-5.1 | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 1592 | 988 |
| LMArena Text | 1461 | — |
| LMArena Creative Writing | 1453 | — |
| LMArena Multi-Turn | 1472 | — |
Frequently asked questions
Is GLM-5.1 better than Pixtral Large?
GLM-5.1 is the stronger model overall, scoring 47.8 to 32.2 on the Noometry Index.
Which is cheaper, GLM-5.1 or Pixtral Large?
GLM-5.1 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Pixtral Large lists at $2 and $6.
Which has the bigger context window?
GLM-5.1 does, with 200K tokens against 128K.
How many benchmarks do GLM-5.1 and Pixtral Large share?
1 benchmark has published results for both models. GLM-5.1 has 41 scored results on Noometry and Pixtral Large has 3.