Devstral 2 2512 vs GLM 5.3 Flash
GLM 5.3 Flash leads Devstral 2 2512 on the Artificial Analysis Intelligence Index, 41.8 to 8.6, and GLM 5.3 Flash costs 4.0x less per output token ($0.50 vs $2.00 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Devstral 2 2512 or GLM 5.3 Flash: which to pick
Only GLM 5.3 Flash has a coding score, 57.7 on the Vibe Coding Index; Devstral 2 2512 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 5
- Devstral 2 2512 only
- 1
- GLM 5.3 Flash only
- 97
- Like-for-like categories
- 3 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only GLM 5.3 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 41.8 against 8.6.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 50.9 against 2.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GLM 5.3 Flash has a GPQA Diamond result, 86.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5.3 Flash has a MMLU Pro result, 86.1%.
Directional only
Web design
Design Arena: websites
No call
Only GLM 5.3 Flash has a Design Arena: websites result, 1272.
Directional only
General
Vals Index
No call
Only GLM 5.3 Flash has a Vals Index result, 50.9%.
Directional only
Long documents
Listed context window
GLM 5.3 Flash
GLM 5.3 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 Flash
Devstral 2 2512 $0.0014, GLM 5.3 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3 Flash
Devstral 2 2512 $1.19, GLM 5.3 Flash $0.02.
Published attempt cost and pass rate
At a glance
- Coding index
- Devstral 2 2512 not benchmarked, GLM 5.3 Flash 57.7 from 6 benchmarks.
- Widest category
- Agentic work, 48.6 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Agentic Index: Devstral 2 2512 2.3 against GLM 5.3 Flash 50.9, 48.6 points apart on a 0 to 100 scale.
- Output price
- Devstral 2 2512 $2.00 against GLM 5.3 Flash $0.50 per million output tokens, 4.0x apart.
- Context window
- Devstral 2 2512 takes 262K tokens, GLM 5.3 Flash 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Devstral 2 2512 | Bars | GLM 5.3 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.8% | Not measured | Only Devstral 2 2512 measured |
| LiveBench coding | Not measured | 80.6% | Only GLM 5.3 Flash measured |
| LMArena WebDev | Not measured | 1607 | Only GLM 5.3 Flash measured |
| AA Coding Index | 31.3 | 71.5 | GLM 5.3 Flash |
| LiveCodeBench (Vals AI) | 51.8% | 80.5% | GLM 5.3 Flash |
| SWE-bench Verified (Vals AI) | 62.8% | 92.0% | GLM 5.3 Flash |
| Terminal-Bench 4 (Vals AI) | Not measured | 37.4% | Only GLM 5.3 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 30.8% | Only GLM 5.3 Flash measured |
| Code migration (Vals AI) | Not measured | 20.5% | Only GLM 5.3 Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GLM 5.3 Flash measured |
| IOI (Vals AI) | Not measured | 52.5% | Only GLM 5.3 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 62.9% | Only GLM 5.3 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 16.0% | Only GLM 5.3 Flash measured |
| SkillsBench (Vals AI) | Not measured | 40.2% | Only GLM 5.3 Flash measured |
| CyberBench (Vals AI) | Not measured | 67.9% | Only GLM 5.3 Flash measured |
| SciCode | Not measured | 51.6% | Only GLM 5.3 Flash measured |
| FrontierCode | Not measured | 31.8% | Only GLM 5.3 Flash measured |
| FrontierSWE | Not measured | 18.1% | Only GLM 5.3 Flash measured |
| ALE-Bench | Not measured | 303.6 | Only GLM 5.3 Flash measured |
| LMArena Text: coding | Not measured | 1507 | Only GLM 5.3 Flash measured |
| LMArena Text: software and IT | Not measured | 1500 | Only GLM 5.3 Flash measured |
| LMArena WebDev: React | Not measured | 1624 | Only GLM 5.3 Flash measured |
| LMArena WebDev: HTML | Not measured | 1577 | Only GLM 5.3 Flash measured |
| LMArena WebDev: from an image | Not measured | 1578 | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.6 | 41.8 | GLM 5.3 Flash |
| Epoch Capabilities Index | Not measured | 153.1 | Only GLM 5.3 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 2.3 | 50.9 | GLM 5.3 Flash |
| LiveBench research | Not measured | 70.1% | Only GLM 5.3 Flash measured |
| LiveBench browser | Not measured | 84.0% | Only GLM 5.3 Flash measured |
| LiveBench long agentic | Not measured | 28.4% | Only GLM 5.3 Flash measured |
| SREBench (Vals AI) | Not measured | 0.8% | Only GLM 5.3 Flash measured |
| Finance Agent (Vals AI) | Not measured | 57.9% | Only GLM 5.3 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 31.6% | Only GLM 5.3 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 45.2% | Only GLM 5.3 Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 10.4% | Only GLM 5.3 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 55.9% | Only GLM 5.3 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only GLM 5.3 Flash measured |
| APEX-Agents | Not measured | 52.8% | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 86.4% | Only GLM 5.3 Flash measured |
| LiveBench reasoning | Not measured | 77.6% | Only GLM 5.3 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 86.0% | Only GLM 5.3 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 91.2% | Only GLM 5.3 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 39.9% | Only GLM 5.3 Flash measured |
| GPQA Diamond (Epoch AI run) | Not measured | 90.2% | Only GLM 5.3 Flash measured |
| ARC-AGI | Not measured | 91.0% | Only GLM 5.3 Flash measured |
| ARC-AGI-2 | Not measured | 65.8% | Only GLM 5.3 Flash measured |
| Chess puzzles | Not measured | 21.0% | Only GLM 5.3 Flash measured |
| Mystery game puzzles | Not measured | 8.0% | Only GLM 5.3 Flash measured |
| LMArena Text: hard prompts | Not measured | 1490 | Only GLM 5.3 Flash measured |
| LMArena Text: expert | Not measured | 1511 | Only GLM 5.3 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1488 | Only GLM 5.3 Flash measured |
| LMArena Vision: diagrams | Not measured | 1317 | Only GLM 5.3 Flash measured |
| LMArena Vision: homework | Not measured | 1318 | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 93.9% | Only GLM 5.3 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 55.8% | Only GLM 5.3 Flash measured |
| FrontierMath, tier 4 | Not measured | 17.1% | Only GLM 5.3 Flash measured |
| ProofBench | Not measured | 21.0% | Only GLM 5.3 Flash measured |
| LMArena Text: math | Not measured | 1503 | Only GLM 5.3 Flash measured |
| LMArena Text: mathematical work | Not measured | 1497 | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.1% | Only GLM 5.3 Flash measured |
| LegalBench (Vals AI) | Not measured | 83.9% | Only GLM 5.3 Flash measured |
| TaxEval (Vals AI) | Not measured | 75.6% | Only GLM 5.3 Flash measured |
| LMArena Text: science | Not measured | 1484 | Only GLM 5.3 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1475 | Only GLM 5.3 Flash measured |
| LMArena Text: legal and government | Not measured | 1473 | Only GLM 5.3 Flash measured |
| LMArena Text: business and finance | Not measured | 1460 | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1272 | Only GLM 5.3 Flash measured |
| Design Arena: UI components | Not measured | 1316 | Only GLM 5.3 Flash measured |
| Design Arena: game dev | Not measured | 1278 | Only GLM 5.3 Flash measured |
| Design Arena: data viz | Not measured | 1262 | Only GLM 5.3 Flash measured |
| Design Arena: 3D | Not measured | 1316 | Only GLM 5.3 Flash measured |
| Design Arena: all code categories | Not measured | 1282 | Only GLM 5.3 Flash measured |
| Design Arena: SVG | Not measured | 1285 | Only GLM 5.3 Flash measured |
| Design Arena: ASCII art | Not measured | 1267 | Only GLM 5.3 Flash measured |
| LiveBench design | Not measured | 77.2% | Only GLM 5.3 Flash measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index28 boards, none shared
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 50.9% | Only GLM 5.3 Flash measured |
| LiveBench data analysis | Not measured | 76.4% | Only GLM 5.3 Flash measured |
| MedScribe (Vals AI) | Not measured | 88.9% | Only GLM 5.3 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 80.0% | Only GLM 5.3 Flash measured |
| Surface Evolver Bench | Not measured | 52.5% | Only GLM 5.3 Flash measured |
| LMArena Text | Not measured | 1471 | Only GLM 5.3 Flash measured |
| LMArena Text: instruction following | Not measured | 1478 | Only GLM 5.3 Flash measured |
| LMArena Text: creative writing | Not measured | 1441 | Only GLM 5.3 Flash measured |
| LMArena Vision | Not measured | 1294 | Only GLM 5.3 Flash measured |
| LMArena Text: English | Not measured | 1474 | Only GLM 5.3 Flash measured |
| LMArena Text: non-English | Not measured | 1462 | Only GLM 5.3 Flash measured |
| LMArena Text: Chinese | Not measured | 1531 | Only GLM 5.3 Flash measured |
| LMArena Text: German | Not measured | 1462 | Only GLM 5.3 Flash measured |
| LMArena Text: Japanese | Not measured | 1444 | Only GLM 5.3 Flash measured |
| LMArena Text: Korean | Not measured | 1436 | Only GLM 5.3 Flash measured |
| LMArena Text: French | Not measured | 1491 | Only GLM 5.3 Flash measured |
| LMArena Text: Spanish | Not measured | 1475 | Only GLM 5.3 Flash measured |
| LMArena Text: Russian | Not measured | 1465 | Only GLM 5.3 Flash measured |
| LMArena Text: Polish | Not measured | 1450 | Only GLM 5.3 Flash measured |
| LMArena Text: multi-turn | Not measured | 1469 | Only GLM 5.3 Flash measured |
| LMArena Text: longer queries | Not measured | 1481 | Only GLM 5.3 Flash measured |
| LMArena Text: writing and language | Not measured | 1455 | Only GLM 5.3 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1440 | Only GLM 5.3 Flash measured |
| LMArena Vision: English | Not measured | 1295 | Only GLM 5.3 Flash measured |
| LMArena Vision: Chinese | Not measured | 1363 | Only GLM 5.3 Flash measured |
| LMArena Vision: reading text | Not measured | 1299 | Only GLM 5.3 Flash measured |
| LMArena Vision: humor | Not measured | 1279 | Only GLM 5.3 Flash measured |
| LMArena Vision: creative writing | Not measured | 1270 | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Devstral 2 2512 | GLM 5.3 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GLM 5.3 Flash costs less
Repository review
50K input + 3K output tokens
GLM 5.3 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 5.3 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Devstral 2 2512 | Z.ai GLM 5.3 Flash |
|---|---|---|
| Maker | Mistral AI | Z.ai |
| Weights | Open weights | Open weights |
| Released | December 9, 2025 | August 26, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.40 | $0.15 |
| Output $/Mtok | $2.00 | $0.50 |
| Coding index | Not benchmarked | 57.7 |
| Independent measurements behind it | 1 | 6 |
| Cost per solved task | $1.19 | $0.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Devstral 2 2512 better than GLM 5.3 Flash for coding?
Only GLM 5.3 Flash has a coding score, 57.7 on the Vibe Coding Index; Devstral 2 2512 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Devstral 2 2512 or GLM 5.3 Flash?
Devstral 2 2512 costs $0.40 per million input tokens and $2.00 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Devstral 2 2512 costs $1.19 and GLM 5.3 Flash $0.02.
Which has the bigger context window, Devstral 2 2512 or GLM 5.3 Flash?
GLM 5.3 Flash, with 1.05M tokens against 262K.
How many benchmarks is the Devstral 2 2512 vs GLM 5.3 Flash comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Devstral 2 2512's coding index rests on 1 independent benchmark and GLM 5.3 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.