DeepSeek V3.1 Terminus vs Extract
Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.0142
- Coding
- No data
- Overall
- No data
- Output $/M
- No data
DeepSeek V3.1 Terminus or Extract: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. DeepSeek V3.1 Terminus has results on AA Coding Index, LiveCodeBench (Artificial Analysis run) and SciCode; Extract has none yet. Compare them on price and context instead.
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
No call
Only DeepSeek V3.1 Terminus has a AA Intelligence Index result, 14.8.
Directional only
Agentic work
AA Agentic Index
No call
Only DeepSeek V3.1 Terminus has a AA Agentic Index result, 6.8.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V3.1 Terminus has a Design Arena: websites result, 1187.
Directional only
Long documents
Listed context window
Extract
Extract takes 1M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Extract
DeepSeek V3.1 Terminus $0.0008, Extract $0.0000 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 Terminus not benchmarked, Extract not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- DeepSeek V3.1 Terminus $1.0142 against Extract Free per million output tokens.
- Context window
- DeepSeek V3.1 Terminus takes 164K tokens, Extract 1M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| AA Coding Index | 43.5 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LiveCodeBench (Artificial Analysis run) | 79.8% | Not measured | Only DeepSeek V3.1 Terminus measured |
| SciCode | 38.0% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.8% | Not measured | Only DeepSeek V3.1 Terminus measured |
| ALE-Bench | 745.2 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: coding | 1425 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: software and IT | 1426 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.8 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| AA Agentic Index | 6.8 | Not measured | Only DeepSeek V3.1 Terminus measured |
| τ²-Bench Telecom | 37.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.2% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Humanity's Last Exam (Artificial Analysis run) | 16.4% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: hard prompts | 1426 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: hard prompts in English | 1432 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Kagi LLM Benchmark | 57.4% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| AA Math Index | 89.7 | Not measured | Only DeepSeek V3.1 Terminus measured |
| AIME 2025 (Artificial Analysis run) | 89.7% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: math | 1402 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 85.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: science | 1451 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: medicine and healthcare | 1468 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: legal and government | 1457 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: business and finance | 1414 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: UI components | 1182 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: game dev | 1131 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: data viz | 1167 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: 3D | 1141 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: all code categories | 1175 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: SVG | 1065 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index15 boards measured
| Benchmark | DeepSeek V3.1 Terminus | Extract | Leader |
|---|---|---|---|
| IFBench | 57.0% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Long context reasoning (AA-LCR) | 69.3% | Not measured | Only DeepSeek V3.1 Terminus measured |
| DTBench | 81.3% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMCA | 28.6% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text | 1419 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: instruction following | 1404 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: creative writing | 1403 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: English | 1429 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: non-English | 1408 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: Russian | 1435 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: Polish | 1427 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: multi-turn | 1411 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: longer queries | 1422 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: writing and language | 1409 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: entertainment and media | 1391 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 31 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
Extract costs less
Repository review
50K input + 3K output tokens
Extract costs less
Agent loop
200K input + 10K output tokens
Extract 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 Terminus | ScaleDown Extract |
|---|---|---|
| Maker | DeepSeek | Scaledown |
| Weights | Open weights | No public weights listed |
| Released | September 22, 2025 | October 13, 2026 |
| Context window | 164K | 1M |
| Input $/Mtok | $0.3063 | $0.04 |
| Output $/Mtok | $1.0142 | Free |
| 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 Terminus better than Extract for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, DeepSeek V3.1 Terminus or Extract?
DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 Terminus or Extract?
Extract, with 1M tokens against 164K.
Has any benchmark tested both DeepSeek V3.1 Terminus and Extract?
No benchmark has tested both yet. DeepSeek V3.1 Terminus has results on AA Coding Index, LiveCodeBench (Artificial Analysis run) and SciCode; Extract has none yet. Compare them on price and context instead. Data as of October 21, 2026.