Model comparison
GLM-4.7 vs Pixtral Large
GLM-4.7 is the stronger model overall, scoring 42.0 to 32.2 on the Noometry Index.
Last verified . 1 shared benchmarks.
Mistral AISummary
- They share 1 benchmark with published results for both. GLM-4.7 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-4.7 leads 60.9 to 32.9.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2 / $6 for Pixtral Large.
- GLM-4.7 accepts more context: 205K tokens versus 128K.
Side by side
| GLM-4.7 | Pixtral Large | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 42.0 | 32.2 |
| Released | 2025-12-22 | 2024-11-01 |
| Weights | Open | Open |
| Context window | 205K | 128K |
| Max output | 131K | 128K |
| Input $ / M tokens | $0.60 | $2 |
| Output $ / M tokens | $2.20 | $6 |
| Results tracked | 36 | 3 |
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Category by category
Coding Not comparable
GLM-4.7: 44.0 (#79), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| LMArena Coding | 1454 | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use Not comparable
GLM-4.7: 26.5 (#103), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Vending-Bench 2 | 2,377 | — |
Reasoning GLM-4.7 leads
GLM-4.7: 24.3 (#164), Pixtral Large: 21.7 (#218)
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| EnigmaEval | — | 0.8% |
| LMArena Hard Prompts | 1443 | — |
| Epoch Capabilities Index | 143.51 | — |
Math Not comparable
GLM-4.7: 38.6 (#135), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| LMArena Math | 1423 | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Not comparable
GLM-4.7: 47.0 (#80), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
| LMArena Expert | 1424 | — |
Multimodal Not comparable
GLM-4.7: —, Pixtral Large: 30.6 (#111)
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |
Multilingual Not comparable
GLM-4.7: 52.8 (#79), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1432 | — |
| LMArena German | 1424 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1399 | — |
| LMArena Russian | 1423 | — |
| LMArena Spanish | 1434 | — |
Instruction Following Not comparable
GLM-4.7: 74.4 (#95), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| LMArena Instruction Following | 1411 | — |
Long Context Not comparable
GLM-4.7: 42.8 (#116), Pixtral Large: —
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
| LMArena Longer Query | 1432 | — |
Writing & Preference GLM-4.7 leads
GLM-4.7: 60.9 (#93), Pixtral Large: 32.9 (#278)
| Benchmark | GLM-4.7 | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 1413 | 988 |
| LMArena Text | 1435 | — |
| LMArena Creative Writing | 1401 | — |
| LMArena Multi-Turn | 1446 | — |
Frequently asked questions
Is GLM-4.7 better than Pixtral Large?
GLM-4.7 is the stronger model overall, scoring 42.0 to 32.2 on the Noometry Index.
Which is cheaper, GLM-4.7 or Pixtral Large?
GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Pixtral Large lists at $2 and $6.
Which has the bigger context window?
GLM-4.7 does, with 205K tokens against 128K.
How many benchmarks do GLM-4.7 and Pixtral Large share?
1 benchmark has published results for both models. GLM-4.7 has 36 scored results on Noometry and Pixtral Large has 3.