DeepSeek V4.1 Flash vs GLM 5V Turbo
DeepSeek V4.1 Flash leads GLM 5V Turbo on the Artificial Analysis Intelligence Index, 24.7 to 23.5, and DeepSeek V4.1 Flash costs 4.8x less per output token ($0.84 vs $4.00 per million). Updated October 22, 2026; 50 benchmarks have a result for both.
vs boards won of 50 shared
DeepSeek V4.1 Flash or GLM 5V Turbo: which to pick
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for work measured by LMArena Vision: Chinese or LMArena Vision: humor, where it leads.
Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BGLM 5V TurboZ.aiNot benchmarked1 independent benchmarkNo cost per solved task
- Shared results
- 50
- DeepSeek V4.1 Flash only
- 51
- GLM 5V Turbo only
- 15
- 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 DeepSeek V4.1 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 24.7 against 23.5.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1308 against 1230.
Same board, both measured
Long documents
Listed context window
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash takes 1.05M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0006, GLM 5V Turbo $0.0032 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, GLM 5V Turbo not benchmarked.
- Widest category
- Coding, 24.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: DeepSeek V4.1 Flash 1612 against GLM 5V Turbo 1356, 40.6 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.84 against GLM 5V Turbo $4.00 per million output tokens, 4.8x apart.
- Context window
- DeepSeek V4.1 Flash takes 1.05M tokens, GLM 5V Turbo 203K.
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 | DeepSeek V4.1 Flash | Bars | GLM 5V Turbo | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 8 | 0 | ||
| General | 21 | 2 | ||
| All shared boards | 48 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | 1402 | DeepSeek V4.1 Flash |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Code migration (Vals AI) | 45.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| SWE-bench Multimodal (Vals AI) | 46.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | 69.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 32.6% | Only GLM 5V Turbo measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: coding | 1502 | 1466 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1496 | 1460 | DeepSeek V4.1 Flash |
| LMArena WebDev: React | 1628 | 1386 | DeepSeek V4.1 Flash |
| LMArena WebDev: HTML | 1612 | 1356 | DeepSeek V4.1 Flash |
| LMArena WebDev: from an image | 1606 | 1425 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 23.5 | DeepSeek V4.1 Flash |
| Epoch Capabilities Index | 155.9 | Not measured | Only DeepSeek V4.1 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1124 | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | Not measured | 1149 | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | Not measured | 1134 | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | Not measured | 1267 | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | Not measured | 957 | Only GLM 5V Turbo measured |
| Design Arena: agents building games | Not measured | 1102 | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | Not measured | 1070 | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | Not measured | 1127 | Only GLM 5V Turbo measured |
| LiveBench research | 86.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench browser | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench long agentic | 40.1% | Not measured | Only DeepSeek V4.1 Flash measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Tax Agent Bench (Vals AI) | 26.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 57.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| τ²-Bench Telecom | Not measured | 98.5% | Only GLM 5V Turbo measured |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| LiveBench reasoning | 86.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.9% | Only GLM 5V Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 17.1% | DeepSeek V4.1 Flash |
| GPQA Diamond (Epoch AI run) | 89.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI | 94.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI-2 | 72.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Chess puzzles | 48.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1483 | 1443 | DeepSeek V4.1 Flash |
| LMArena Text: expert | 1501 | 1453 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1488 | 1456 | DeepSeek V4.1 Flash |
| LMArena Vision: diagrams | 1297 | 1286 | DeepSeek V4.1 Flash |
| LMArena Vision: homework | 1307 | 1273 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tiers 1 to 3 | 67.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProofBench | 54.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: math | 1478 | 1442 | DeepSeek V4.1 Flash |
| LMArena Text: mathematical work | 1485 | 1447 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| SimpleQA Verified | 42.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: science | 1469 | 1448 | DeepSeek V4.1 Flash |
| LMArena Text: medicine and healthcare | 1484 | 1433 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1443 | 1436 | DeepSeek V4.1 Flash |
| LMArena Text: business and finance | 1461 | 1435 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | 1230 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1312 | 1210 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1330 | 1218 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1291 | 1202 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1355 | 1208 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1320 | 1228 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1245 | 1151 | DeepSeek V4.1 Flash |
| Design Arena: ASCII art | 1265 | 1117 | DeepSeek V4.1 Flash |
| LiveBench design | 79.2% | Not measured | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index212
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | 64.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | 47.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | 85.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IFBench | Not measured | 61.1% | Only GLM 5V Turbo measured |
| Long context reasoning (AA-LCR) | 84.0% | 70.3% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMCA | 47.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Surface Evolver Bench | 46.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1464 | 1437 | DeepSeek V4.1 Flash |
| LMArena Text: instruction following | 1473 | 1423 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1437 | 1417 | DeepSeek V4.1 Flash |
| LMArena Vision | 1278 | 1264 | DeepSeek V4.1 Flash |
| LMArena Text: English | 1473 | 1454 | DeepSeek V4.1 Flash |
| LMArena Text: non-English | 1449 | 1420 | DeepSeek V4.1 Flash |
| LMArena Text: Chinese | 1501 | 1491 | DeepSeek V4.1 Flash |
| LMArena Text: German | 1470 | 1422 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1432 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Korean | 1436 | 1397 | DeepSeek V4.1 Flash |
| LMArena Text: French | 1465 | 1443 | DeepSeek V4.1 Flash |
| LMArena Text: Spanish | 1459 | 1452 | DeepSeek V4.1 Flash |
| LMArena Text: Russian | 1467 | 1432 | DeepSeek V4.1 Flash |
| LMArena Text: Polish | 1457 | 1432 | DeepSeek V4.1 Flash |
| LMArena Text: multi-turn | 1461 | 1431 | DeepSeek V4.1 Flash |
| LMArena Text: longer queries | 1473 | 1438 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1450 | 1420 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1445 | 1407 | DeepSeek V4.1 Flash |
| LMArena Vision: English | 1288 | 1274 | DeepSeek V4.1 Flash |
| LMArena Vision: Chinese | 1327 | 1329 | GLM 5V Turbo |
| LMArena Vision: reading text | 1282 | 1270 | DeepSeek V4.1 Flash |
| LMArena Vision: humor | 1260 | 1268 | GLM 5V Turbo |
| LMArena Vision: captioning | Not measured | 1264 | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | Not measured | 1241 | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | 1275 | 1252 | DeepSeek V4.1 Flash |
| LMArena Document | Not measured | 1416 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GLM 5V Turbo | 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
DeepSeek V4.1 Flash$0.0006Fits in one request
GLM 5V Turbo$0.0032Fits in one request
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash$0.014Fits in one request
GLM 5V Turbo$0.072Fits in one request
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash$0.053Fits in one request
GLM 5V Turbo$0.280Exceeds the context window
DeepSeek V4.1 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 | DeepSeek V4.1 Flash | Z.ai GLM 5V Turbo |
|---|---|---|
| Maker | DeepSeek | Z.ai |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | April 1, 2026 |
| Context window | 1.05M | 203K |
| Input $/Mtok | $0.2225 | $1.20 |
| Output $/Mtok | $0.84 | $4.00 |
| Coding index | 62.5 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than GLM 5V Turbo for coding?
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding. Pick GLM 5V Turbo for work measured by LMArena Vision: Chinese or LMArena Vision: humor, where it leads.
Which is cheaper, DeepSeek V4.1 Flash or GLM 5V Turbo?
DeepSeek V4.1 Flash costs $0.2225 per million input tokens and $0.84 per million output tokens; GLM 5V Turbo costs $1.20 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4.1 Flash or GLM 5V Turbo?
DeepSeek V4.1 Flash, with 1.05M tokens against 203K.
How many benchmarks is the DeepSeek V4.1 Flash vs GLM 5V Turbo comparison based on?
50 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4.1 Flash's coding index rests on 5 independent benchmarks and GLM 5V Turbo's on 1. Where only one model has a result, the page says so instead of naming a winner.