GLM 5V Turbo vs Mistral Large 4
Mistral Large 4 leads GLM 5V Turbo on the Artificial Analysis Intelligence Index, 38.4 to 23.5, at about the same output price ($4.18 vs $4.00 per million). Updated October 22, 2026; 42 benchmarks have a result for both.
GLM 5V Turbo or Mistral Large 4: which to pick
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for output tokens 1.0x cheaper ($4.00 vs $4.18 per million) and work measured by LMArena Text: expert or LMArena Text: hard prompts in English, where it leads.
- Shared results
- 42
- GLM 5V Turbo only
- 23
- Mistral Large 4 only
- 40
- Like-for-like categories
- 7 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 Mistral Large 4 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 23.5.
Same board, both measured
Web design
Design Arena: websites
Mistral Large 4
Mistral Large 4 leads, 1258 against 1230.
Same board, both measured
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5V Turbo
GLM 5V Turbo $0.0032, Mistral Large 4 $0.0034 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, Mistral Large 4 56.4 from 5 benchmarks.
- Widest category
- Intelligence, 14.9 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena WebDev: React: GLM 5V Turbo 1386 against Mistral Large 4 1559, 28.7 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against Mistral Large 4 $4.18 per million output tokens, 1.0x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, Mistral Large 4 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 | GLM 5V Turbo | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 2 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 2 | 2 | ||
| Web design | 0 | 8 | ||
| General | 8 | 9 | ||
| All shared boards | 12 | 30 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | 1402 | 1543 | Mistral Large 4 |
| Terminal-Bench 4 (Vals AI) | Not measured | 27.8% | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 78.4% | Only Mistral Large 4 measured |
| Code migration (Vals AI) | Not measured | 30.6% | Only Mistral Large 4 measured |
| IOI (Vals AI) | Not measured | 45.3% | Only Mistral Large 4 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.1% | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 14.3% | Only Mistral Large 4 measured |
| SciCode | Not measured | 54.2% | Only Mistral Large 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | Not measured | Only GLM 5V Turbo measured |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| ALE-Bench | Not measured | 1213.2 | Only Mistral Large 4 measured |
| LMArena Text: coding | 1466 | 1478 | Mistral Large 4 |
| LMArena Text: software and IT | 1460 | 1467 | Mistral Large 4 |
| LMArena WebDev: React | 1386 | 1559 | Mistral Large 4 |
| LMArena WebDev: HTML | 1356 | 1487 | Mistral Large 4 |
| LMArena WebDev: from an image | 1425 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 38.4 | Mistral Large 4 |
| Epoch Capabilities Index | Not measured | 150.0 | Only Mistral Large 4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1124 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | 1149 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | 1134 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | 1267 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | 957 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building games | 1102 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | 1060 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1126 | Not measured | Only GLM 5V Turbo measured |
| LiveBench research | Not measured | 28.1% | Only Mistral Large 4 measured |
| LiveBench browser | Not measured | 8.0% | Only Mistral Large 4 measured |
| LiveBench long agentic | Not measured | 11.8% | Only Mistral Large 4 measured |
| Finance Agent (Vals AI) | Not measured | 54.7% | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.4% | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | Not measured | 31.7% | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 17.5% | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 56.2% | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| τ²-Bench Telecom | 98.5% | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 83.9% | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | Not measured | 12.2% | Only Mistral Large 4 measured |
| GPQA Diamond (Artificial Analysis run) | 80.9% | Not measured | Only GLM 5V Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 35.0% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | Not measured | 88.1% | Only Mistral Large 4 measured |
| Chess puzzles | Not measured | 33.0% | Only Mistral Large 4 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | 1443 | 1444 | Mistral Large 4 |
| LMArena Text: expert | 1453 | 1444 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1456 | 1442 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | 1288 | Mistral Large 4 |
| LMArena Vision: homework | 1273 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 98.3% | Only Mistral Large 4 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 58.6% | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | Not measured | 26.8% | Only Mistral Large 4 measured |
| ProofBench | Not measured | 10.0% | Only Mistral Large 4 measured |
| LMArena Text: math | 1442 | 1469 | Mistral Large 4 |
| LMArena Text: mathematical work | 1447 | 1462 | Mistral Large 4 |
| MathArena | Not measured | 26.7% | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 40.7% | Only Mistral Large 4 measured |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | 1448 | Mistral Large 4 |
| LMArena Text: medicine and healthcare | 1433 | 1433 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1425 | GLM 5V Turbo |
| LMArena Text: business and finance | 1435 | 1439 | Mistral Large 4 |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1258 | Mistral Large 4 |
| Design Arena: UI components | 1210 | 1273 | Mistral Large 4 |
| Design Arena: game dev | 1218 | 1225 | Mistral Large 4 |
| Design Arena: data viz | 1202 | 1275 | Mistral Large 4 |
| Design Arena: 3D | 1208 | 1252 | Mistral Large 4 |
| Design Arena: all code categories | 1227 | 1259 | Mistral Large 4 |
| Design Arena: SVG | 1150 | 1232 | Mistral Large 4 |
| Design Arena: ASCII art | 1116 | 1202 | Mistral Large 4 |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index89
| Benchmark | GLM 5V Turbo | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Mistral Large 4 measured |
| MedScribe (Vals AI) | Not measured | 80.4% | Only Mistral Large 4 measured |
| IFBench | 61.1% | Not measured | Only GLM 5V Turbo measured |
| Long context reasoning (AA-LCR) | 70.3% | 81.3% | Mistral Large 4 |
| DTBench | Not measured | 88.2% | Only Mistral Large 4 measured |
| LMCA | Not measured | 35.8% | Only Mistral Large 4 measured |
| Surface Evolver Bench | Not measured | 28.1% | Only Mistral Large 4 measured |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| LMArena Text | 1437 | 1431 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1422 | GLM 5V Turbo |
| LMArena Text: creative writing | 1417 | 1363 | GLM 5V Turbo |
| LMArena Vision | 1264 | 1272 | Mistral Large 4 |
| LMArena Text: English | 1454 | 1433 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1422 | Mistral Large 4 |
| LMArena Text: Chinese | 1491 | 1492 | Mistral Large 4 |
| LMArena Text: German | 1422 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Japanese | Not measured | 1415 | Only Mistral Large 4 measured |
| LMArena Text: Korean | 1397 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: French | 1443 | 1492 | Mistral Large 4 |
| LMArena Text: Spanish | 1452 | 1455 | Mistral Large 4 |
| LMArena Text: Russian | 1432 | 1417 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | 1431 | 1435 | Mistral Large 4 |
| LMArena Text: longer queries | 1438 | 1428 | GLM 5V Turbo |
| LMArena Text: writing and language | 1420 | 1386 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1378 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | 1283 | Mistral Large 4 |
| LMArena Vision: Chinese | 1329 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | 1270 | 1284 | Mistral Large 4 |
| LMArena Vision: humor | 1268 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | 1252 | Not measured | Only GLM 5V Turbo measured |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | Mistral Large 4 | 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 5V Turbo costs less
Repository review
50K input + 3K output tokens
GLM 5V Turbo costs less
Agent loop
200K input + 10K output tokens
GLM 5V Turbo 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 | Z.ai GLM 5V Turbo | Mistral Large 4 |
|---|---|---|
| Maker | Z.ai | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | April 1, 2026 | October 6, 2026 |
| Context window | 203K | 1.05M |
| Input $/Mtok | $1.20 | $1.36 |
| Output $/Mtok | $4.00 | $4.18 |
| Coding index | Not benchmarked | 56.4 |
| Independent measurements behind it | 1 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than Mistral Large 4 for coding?
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding. Pick GLM 5V Turbo for output tokens 1.0x cheaper ($4.00 vs $4.18 per million) and work measured by LMArena Text: expert or LMArena Text: hard prompts in English, where it leads.
Which is cheaper, GLM 5V Turbo or Mistral Large 4?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5V Turbo or Mistral Large 4?
Mistral Large 4, with 1.05M tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs Mistral Large 4 comparison based on?
42 benchmarks have a result for both models as of October 22, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Mistral Large 4's on 5. Where only one model has a result, the page says so instead of naming a winner.