Model comparison
Devstral Small 2505 vs GLM-4.6
GLM-4.6 is the stronger model overall, scoring 41.4 to 34.3 on the Noometry Index. Devstral Small 2505 costs 6.7× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AISummary
- They share 4 benchmarks with published results for both. Devstral Small 2505 scores higher in 0 categories and GLM-4.6 in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6 leads 23.7 to 19.7.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 37.7% for Devstral Small 2505 and 47.4% for GLM-4.6.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- GLM-4.6 accepts more context: 205K tokens versus 128K.
Side by side
| Devstral Small 2505 | GLM-4.6 | |
|---|---|---|
| Provider | Mistral AI | Z.ai (Zhipu) |
| Noometry Index | 34.3 | 41.4 |
| Released | 2025-05-07 | 2025-09-30 |
| Weights | Open | Open |
| Context window | 128K | 205K |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.10 | $0.60 |
| Output $ / M tokens | $0.30 | $2.20 |
| Results tracked | 4 | 29 |
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Category by category
Coding GLM-4.6 leads
Devstral Small 2505: 38.9 (#166), GLM-4.6: 40.1 (#148)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| SWE-bench Verified (bash only) | 56.4% | 55.4% |
| SciCode | 28.8% | 38.4% |
| LMArena WebDev | — | 1340 |
| LMArena Coding | — | 1449 |
| ALE-Bench | — | 340.82 |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, GLM-4.6: 32.3 (#66)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| Terminal-Bench | — | 24.5% |
| Berkeley Function Calling Leaderboard | — | 72.4% |
Reasoning GLM-4.6 leads
Devstral Small 2505: 19.7 (#252), GLM-4.6: 23.7 (#172)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| Kagi LLM Benchmark | 37.7% | 47.4% |
| CritPt | 0% | 1.1% |
| LMArena Hard Prompts | — | 1440 |
Math Not comparable
Devstral Small 2505: —, GLM-4.6: 39.1 (#111)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| LMArena Math | — | 1432 |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
Devstral Small 2505: —, GLM-4.6: 40.2 (#124)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| Vectara Hallucination Rate | — | 9.5% |
| LMArena Expert | — | 1431 |
Multilingual Not comparable
Devstral Small 2505: —, GLM-4.6: 53.5 (#66)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| LMArena Non-English | — | 1426 |
| LMArena Chinese | — | 1499 |
| LMArena French | — | 1459 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1393 |
| LMArena Korean | — | 1400 |
| LMArena Russian | — | 1419 |
| LMArena Spanish | — | 1436 |
Instruction Following Not comparable
Devstral Small 2505: —, GLM-4.6: 74.3 (#98)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | — | 1410 |
Long Context Not comparable
Devstral Small 2505: —, GLM-4.6: 43.4 (#94)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | — | 1422 |
Writing & Preference Not comparable
Devstral Small 2505: —, GLM-4.6: 61.1 (#90)
| Benchmark | Devstral Small 2505 | GLM-4.6 |
|---|---|---|
| LMArena Text | — | 1440 |
| LMArena Creative Writing | — | 1411 |
| EQ-Bench Creative Writing | — | 1411 |
| LMArena Multi-Turn | — | 1427 |
Frequently asked questions
Is Devstral Small 2505 better than GLM-4.6?
GLM-4.6 is the stronger model overall, scoring 41.4 to 34.3 on the Noometry Index. Devstral Small 2505 costs 6.7× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.
Which is cheaper, Devstral Small 2505 or GLM-4.6?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.
Is Devstral Small 2505 or GLM-4.6 better for coding?
GLM-4.6 scores higher on coding benchmarks: 40.1 versus 38.9 in the Noometry coding category.
Which has the bigger context window?
GLM-4.6 does, with 205K tokens against 128K.
How many benchmarks do Devstral Small 2505 and GLM-4.6 share?
4 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and GLM-4.6 has 29.