DeepSeek V3.1 vs GLM 5 Turbo
GLM 5 Turbo leads DeepSeek V3.1 on the Artificial Analysis Intelligence Index, 26.6 to 13.7, and DeepSeek V3.1 costs 2.7x less per output token ($1.50 vs $4.00 per million). Updated October 22, 2026; 8 benchmarks have a result for both.
DeepSeek V3.1 or GLM 5 Turbo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 for output tokens 2.7x cheaper ($1.50 vs $4.00 per million) and work measured by AA Intelligence Index or Design Arena: websites, where it leads.
- Shared results
- 8
- DeepSeek V3.1 only
- 3
- GLM 5 Turbo only
- 8
- Like-for-like categories
- 2 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GLM 5 Turbo
GLM 5 Turbo leads, 26.6 against 13.7.
Same board, both measured
Web design
Design Arena: websites
GLM 5 Turbo
GLM 5 Turbo leads, 1262 against 1122.
Same board, both measured
Long documents
Listed context window
GLM 5 Turbo
GLM 5 Turbo takes 203K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1
DeepSeek V3.1 $0.0013, GLM 5 Turbo $0.0032 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, GLM 5 Turbo not benchmarked.
- Widest category
- Web design, 21.5 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: SVG: DeepSeek V3.1 967 against GLM 5 Turbo 1205, 29.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against GLM 5 Turbo $4.00 per million output tokens, 2.7x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, GLM 5 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 V3.1 | Bars | GLM 5 Turbo | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Web design | 0 | 7 | ||
| All shared boards | 0 | 8 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 33.3% | Only GLM 5 Turbo measured |
| ALE-Bench | Not measured | 634.0 | Only GLM 5 Turbo measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 26.6 | GLM 5 Turbo |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 98.5% | Only GLM 5 Turbo measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.7% | Only GLM 5 Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 27.8% | Only GLM 5 Turbo measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 1122 | 1262 | GLM 5 Turbo |
| Design Arena: UI components | 1085 | 1260 | GLM 5 Turbo |
| Design Arena: game dev | 1084 | 1248 | GLM 5 Turbo |
| Design Arena: data viz | 1096 | 1264 | GLM 5 Turbo |
| Design Arena: 3D | 1077 | 1247 | GLM 5 Turbo |
| Design Arena: all code categories | 1112 | 1261 | GLM 5 Turbo |
| Design Arena: SVG | 967 | 1205 | GLM 5 Turbo |
| Design Arena: ASCII art | Not measured | 1160 | Only GLM 5 Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 Turbo | Leader |
|---|---|---|---|
| IFBench | Not measured | 73.2% | Only GLM 5 Turbo measured |
| Long context reasoning (AA-LCR) | Not measured | 71.7% | Only GLM 5 Turbo measured |
| DTBench | 82.7% | Not measured | Only DeepSeek V3.1 measured |
| LMCA | 24.3% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | GLM 5 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 V3.1 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 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 V3.1 | Z.ai GLM 5 Turbo |
|---|---|---|
| Maker | DeepSeek | Z.ai |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2025 | March 15, 2026 |
| Context window | 164K | 203K |
| Input $/Mtok | $0.55 | $1.20 |
| Output $/Mtok | $1.50 | $4.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 better than GLM 5 Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for output tokens 2.7x cheaper ($1.50 vs $4.00 per million) and work measured by AA Intelligence Index or Design Arena: websites, where it leads.
Which is cheaper, DeepSeek V3.1 or GLM 5 Turbo?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; GLM 5 Turbo costs $1.20 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 or GLM 5 Turbo?
GLM 5 Turbo, with 203K tokens against 164K.
How many benchmarks is the DeepSeek V3.1 vs GLM 5 Turbo comparison based on?
8 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and GLM 5 Turbo's on 0. Where only one model has a result, the page says so instead of naming a winner.