DeepSeek V4 Flash Vision Exp vs GLM 4.6
Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 37.6 for DeepSeek V4 Flash Vision Exp.
Pick DeepSeek V4 Flash Vision Exp when output tokens cost 3.4x less, or when the context window is larger, 1.05M against 205K tokens.
- Shared results
- 5
- DeepSeek V4 Flash Vision Exp only
- 9
- GLM 4.6 only
- 61
- Like-for-like categories
- 4 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
GLM 4.6
GLM 4.6 scores 52.2 against 37.6.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp leads, 34.8 against 18.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash Vision Exp has a AA Agentic Index result, 47.5.
Directional only
Reasoning
GPQA Diamond
No call
Only GLM 4.6 has a GPQA Diamond result, 74.5%.
Directional only
Math
AIME
No call
Only GLM 4.6 has a AIME result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 4.6 has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
No call
Only GLM 4.6 has a Design Arena: websites result, 1174.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp $0.0005, GLM 4.6 $0.0016 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp 37.6 from 1 benchmark, GLM 4.6 52.2 from 2 benchmarks.
- Widest category
- General, 27.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): DeepSeek V4 Flash Vision Exp 81.3% against GLM 4.6 54.0%, 27.3 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash Vision Exp $0.6468 against GLM 4.6 $2.20 per million output tokens, 3.4x apart.
- Context window
- DeepSeek V4 Flash Vision Exp takes 1.05M tokens, GLM 4.6 205K.
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 Flash Vision Exp | Bars | GLM 4.6 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 5 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 68.2% | Only GLM 4.6 measured |
| LiveBench coding | 37.6% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LMArena WebDev | Not measured | 1341 | Only GLM 4.6 measured |
| AA Coding Index | 65.0 | 45.8 | DeepSeek V4 Flash Vision Exp |
| LiveCodeBench (Vals AI) | Not measured | 81.0% | Only GLM 4.6 measured |
| Vibe Code Bench (Vals AI) | Not measured | 3.1% | Only GLM 4.6 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 69.5% | Only GLM 4.6 measured |
| SciCode | 49.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 28.8% | Only GLM 4.6 measured |
| Terminal-Bench | Not measured | 24.5% | Only GLM 4.6 measured |
| ALE-Bench | Not measured | 340.8 | Only GLM 4.6 measured |
| LMArena Text: coding | Not measured | 1449 | Only GLM 4.6 measured |
| LMArena Text: software and IT | Not measured | 1455 | Only GLM 4.6 measured |
| LMArena WebDev: HTML | Not measured | 1350 | Only GLM 4.6 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | 18.5 | DeepSeek V4 Flash Vision Exp |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Design Arena: agents building full-stack apps | Not measured | 1029 | Only GLM 4.6 measured |
| Design Arena: agents building mobile apps | Not measured | 1096 | Only GLM 4.6 measured |
| Design Arena: agents building Android apps | Not measured | 1090 | Only GLM 4.6 measured |
| Design Arena: agents building Godot games | Not measured | 1180 | Only GLM 4.6 measured |
| LiveBench research | 69.2% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench browser | 64.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench long agentic | 39.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| τ²-Bench Telecom | Not measured | 76.9% | Only GLM 4.6 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 74.5% | Only GLM 4.6 measured |
| LiveBench reasoning | 85.4% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| GPQA Diamond (Artificial Analysis run) | 91.3% | 78.0% | DeepSeek V4 Flash Vision Exp |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 14.5% | DeepSeek V4 Flash Vision Exp |
| LMArena Text: hard prompts | Not measured | 1440 | Only GLM 4.6 measured |
| LMArena Text: expert | Not measured | 1432 | Only GLM 4.6 measured |
| LMArena Text: hard prompts in English | Not measured | 1445 | Only GLM 4.6 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| AIME | Not measured | 92.7% | Only GLM 4.6 measured |
| MGSM (Vals AI) | Not measured | 89.8% | Only GLM 4.6 measured |
| AA Math Index | Not measured | 86.0 | Only GLM 4.6 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 86.0% | Only GLM 4.6 measured |
| LMArena Text: math | Not measured | 1432 | Only GLM 4.6 measured |
| LMArena Text: mathematical work | Not measured | 1447 | Only GLM 4.6 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.2% | Only GLM 4.6 measured |
| LegalBench (Vals AI) | Not measured | 79.6% | Only GLM 4.6 measured |
| CorpFin (Vals AI) | Not measured | 56.8% | Only GLM 4.6 measured |
| TaxEval (Vals AI) | Not measured | 66.2% | Only GLM 4.6 measured |
| MedQA (Vals AI) | Not measured | 92.2% | Only GLM 4.6 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 82.9% | Only GLM 4.6 measured |
| LMArena Text: science | Not measured | 1456 | Only GLM 4.6 measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only GLM 4.6 measured |
| LMArena Text: legal and government | Not measured | 1448 | Only GLM 4.6 measured |
| LMArena Text: business and finance | Not measured | 1416 | Only GLM 4.6 measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1174 | Only GLM 4.6 measured |
| Design Arena: UI components | Not measured | 1147 | Only GLM 4.6 measured |
| Design Arena: game dev | Not measured | 1151 | Only GLM 4.6 measured |
| Design Arena: data viz | Not measured | 1161 | Only GLM 4.6 measured |
| Design Arena: 3D | Not measured | 1129 | Only GLM 4.6 measured |
| Design Arena: all code categories | Not measured | 1166 | Only GLM 4.6 measured |
| Design Arena: SVG | Not measured | 1108 | Only GLM 4.6 measured |
| LiveBench design | 70.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| IFBench | Not measured | 43.4% | Only GLM 4.6 measured |
| Long context reasoning (AA-LCR) | 81.3% | 54.0% | DeepSeek V4 Flash Vision Exp |
| LMArena Text | Not measured | 1440 | Only GLM 4.6 measured |
| LMArena Text: instruction following | Not measured | 1410 | Only GLM 4.6 measured |
| LMArena Text: creative writing | Not measured | 1412 | Only GLM 4.6 measured |
| LMArena Text: English | Not measured | 1449 | Only GLM 4.6 measured |
| LMArena Text: non-English | Not measured | 1426 | Only GLM 4.6 measured |
| LMArena Text: Chinese | Not measured | 1499 | Only GLM 4.6 measured |
| LMArena Text: German | Not measured | 1447 | Only GLM 4.6 measured |
| LMArena Text: Japanese | Not measured | 1393 | Only GLM 4.6 measured |
| LMArena Text: Korean | Not measured | 1400 | Only GLM 4.6 measured |
| LMArena Text: French | Not measured | 1459 | Only GLM 4.6 measured |
| LMArena Text: Spanish | Not measured | 1436 | Only GLM 4.6 measured |
| LMArena Text: Russian | Not measured | 1418 | Only GLM 4.6 measured |
| LMArena Text: Polish | Not measured | 1447 | Only GLM 4.6 measured |
| LMArena Text: multi-turn | Not measured | 1427 | Only GLM 4.6 measured |
| LMArena Text: longer queries | Not measured | 1422 | Only GLM 4.6 measured |
| LMArena Text: writing and language | Not measured | 1415 | Only GLM 4.6 measured |
| LMArena Text: entertainment and media | Not measured | 1409 | Only GLM 4.6 measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GLM 4.6 | 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 Flash Vision Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash Vision Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash Vision Exp 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 Flash Vision Exp | Z.ai GLM 4.6 |
|---|---|---|
| Maker | DeepSeek | Z.ai |
| Weights | Open weights | Open weights |
| Released | August 21, 2026 | September 30, 2025 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $0.2156 | $0.55 |
| Output $/Mtok | $0.6468 | $2.20 |
| Coding index | 37.6 | 52.2 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than GLM 4.6 for coding?
Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 37.6 for DeepSeek V4 Flash Vision Exp. Pick DeepSeek V4 Flash Vision Exp when output tokens cost 3.4x less, or when the context window is larger, 1.05M against 205K tokens.
Which is cheaper, DeepSeek V4 Flash Vision Exp or GLM 4.6?
DeepSeek V4 Flash Vision Exp costs $0.2156 per million input tokens and $0.6468 per million output tokens; GLM 4.6 costs $0.55 and $2.20. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4 Flash Vision Exp or GLM 4.6?
DeepSeek V4 Flash Vision Exp, with 1.05M tokens against 205K.
How many benchmarks is the DeepSeek V4 Flash Vision Exp vs GLM 4.6 comparison based on?
5 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash Vision Exp's coding index rests on 1 independent benchmark and GLM 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.