DeepSeek V3.1 Terminus vs DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads DeepSeek V3.1 Terminus on the Artificial Analysis Intelligence Index, 30.4 to 14.8, and DeepSeek V3.1 Terminus costs 2.7x less per output token ($1.0142 vs $2.716 per million). Updated October 21, 2026; 34 benchmarks have a result for both.
DeepSeek V3.1 Terminus or DeepSeek V4 Pro 0423: which to pick
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 Terminus for output tokens 2.7x cheaper ($1.0142 vs $2.716 per million) and work measured by Kagi LLM Benchmark or LMArena Text: medicine and healthcare, where it leads.
- Shared results
- 34
- DeepSeek V3.1 Terminus only
- 11
- DeepSeek V4 Pro 0423 only
- 50
- Like-for-like categories
- 8 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 Pro 0423 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 30.4 against 14.8.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 26.3 against 6.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only DeepSeek V4 Pro 0423 has a GPQA Diamond result, 89.4%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V4 Pro 0423 has a MMLU Pro result, 87.3%.
Directional only
Web design
Design Arena: websites
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 1234 against 1187.
Same board, both measured
Long documents
Listed context window
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus $0.0008, DeepSeek V4 Pro 0423 $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0423 has the number, $0.57.
Directional only
At a glance
- Coding index
- DeepSeek V3.1 Terminus not benchmarked, DeepSeek V4 Pro 0423 38.7 from 5 benchmarks.
- Widest category
- Agentic work, 19.5 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Agentic Index: DeepSeek V3.1 Terminus 6.8 against DeepSeek V4 Pro 0423 26.3, 19.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 Terminus $1.0142 against DeepSeek V4 Pro 0423 $2.716 per million output tokens, 2.7x apart.
- Context window
- DeepSeek V3.1 Terminus takes 164K tokens, DeepSeek V4 Pro 0423 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 | DeepSeek V3.1 Terminus | Bars | DeepSeek V4 Pro 0423 | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 2 | ||
| Math | 0 | 1 | ||
| Knowledge | 1 | 3 | ||
| Web design | 0 | 7 | ||
| General | 0 | 13 | ||
| All shared boards | 2 | 32 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1447 | Only DeepSeek V4 Pro 0423 measured |
| AA Coding Index | 43.5 | 59.4 | DeepSeek V4 Pro 0423 |
| LiveCodeBench (Vals AI) | Not measured | 87.5% | Only DeepSeek V4 Pro 0423 measured |
| SWE-bench Verified (Vals AI) | Not measured | 77.4% | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 11.1% | Only DeepSeek V4 Pro 0423 measured |
| Vibe Code Bench (Vals AI) | Not measured | 49.9% | Only DeepSeek V4 Pro 0423 measured |
| Code migration (Vals AI) | Not measured | 26.2% | Only DeepSeek V4 Pro 0423 measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 50.2% | Only DeepSeek V4 Pro 0423 measured |
| SkillsBench (Vals AI) | Not measured | 51.3% | Only DeepSeek V4 Pro 0423 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 |
| FrontierCode | Not measured | 17.6% | Only DeepSeek V4 Pro 0423 measured |
| WeirdML | Not measured | 48.9% | Only DeepSeek V4 Pro 0423 measured |
| ALE-Bench | 745.2 | 1006.1 | DeepSeek V4 Pro 0423 |
| LMArena Text: coding | 1425 | 1470 | DeepSeek V4 Pro 0423 |
| LMArena Text: software and IT | 1426 | 1469 | DeepSeek V4 Pro 0423 |
| LMArena WebDev: React | Not measured | 1441 | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: HTML | Not measured | 1435 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.8 | 30.4 | DeepSeek V4 Pro 0423 |
| Epoch Capabilities Index | Not measured | 149.1 | Only DeepSeek V4 Pro 0423 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| AA Agentic Index | 6.8 | 26.3 | DeepSeek V4 Pro 0423 |
| Design Arena: agents building web apps | Not measured | 1000 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building full-stack apps | Not measured | 948 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building Godot games | Not measured | 1059 | Only DeepSeek V4 Pro 0423 measured |
| Finance Agent (Vals AI) | Not measured | 44.1% | Only DeepSeek V4 Pro 0423 measured |
| Tax Agent Bench (Vals AI) | Not measured | 25.2% | Only DeepSeek V4 Pro 0423 measured |
| Legal Research Bench (Vals AI) | Not measured | 23.1% | Only DeepSeek V4 Pro 0423 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 51.6% | Only DeepSeek V4 Pro 0423 measured |
| τ²-Bench Telecom | 37.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Vending-Bench 2 | Not measured | $3,285 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 89.4% | Only DeepSeek V4 Pro 0423 measured |
| 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 |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only DeepSeek V4 Pro 0423 measured |
| Chess puzzles | Not measured | 19.0% | Only DeepSeek V4 Pro 0423 measured |
| Mystery game puzzles | Not measured | 17.0% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts | 1426 | 1461 | DeepSeek V4 Pro 0423 |
| LMArena Text: expert | Not measured | 1463 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts in English | 1432 | 1466 | DeepSeek V4 Pro 0423 |
| Kagi LLM Benchmark | 57.4% | 53.5% | DeepSeek V3.1 Terminus |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | 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 |
| OTIS Mock AIME | Not measured | 96.7% | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 45.3% | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tier 4 | Not measured | 2.4% | Only DeepSeek V4 Pro 0423 measured |
| ProofBench | Not measured | 16.0% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: math | 1402 | 1443 | DeepSeek V4 Pro 0423 |
| LMArena Text: mathematical work | Not measured | 1455 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.3% | Only DeepSeek V4 Pro 0423 measured |
| LegalBench (Vals AI) | Not measured | 80.3% | Only DeepSeek V4 Pro 0423 measured |
| CaseLaw (Vals AI) | Not measured | 59.4% | Only DeepSeek V4 Pro 0423 measured |
| CorpFin (Vals AI) | Not measured | 61.4% | Only DeepSeek V4 Pro 0423 measured |
| TaxEval (Vals AI) | Not measured | 72.1% | Only DeepSeek V4 Pro 0423 measured |
| MedCode (Vals AI) | Not measured | 40.5% | Only DeepSeek V4 Pro 0423 measured |
| MMLU Pro (Artificial Analysis run) | 85.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| SimpleQA Verified | Not measured | 47.0% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: science | 1451 | 1470 | DeepSeek V4 Pro 0423 |
| LMArena Text: medicine and healthcare | 1468 | 1466 | DeepSeek V3.1 Terminus |
| LMArena Text: legal and government | 1457 | 1464 | DeepSeek V4 Pro 0423 |
| LMArena Text: business and finance | 1414 | 1443 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | 1234 | DeepSeek V4 Pro 0423 |
| Design Arena: UI components | 1182 | 1222 | DeepSeek V4 Pro 0423 |
| Design Arena: game dev | 1131 | 1229 | DeepSeek V4 Pro 0423 |
| Design Arena: data viz | 1167 | 1203 | DeepSeek V4 Pro 0423 |
| Design Arena: 3D | 1141 | 1254 | DeepSeek V4 Pro 0423 |
| Design Arena: all code categories | 1175 | 1240 | DeepSeek V4 Pro 0423 |
| Design Arena: SVG | 1065 | 1140 | DeepSeek V4 Pro 0423 |
| Design Arena: ASCII art | Not measured | 1149 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index013
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 62.9% | Only DeepSeek V4 Pro 0423 measured |
| MedScribe (Vals AI) | Not measured | 75.1% | Only DeepSeek V4 Pro 0423 measured |
| 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% | 90.7% | DeepSeek V4 Pro 0423 |
| LMCA | 28.6% | 41.2% | DeepSeek V4 Pro 0423 |
| Surface Evolver Bench | Not measured | 40.0% | Only DeepSeek V4 Pro 0423 measured |
| CL-bench Life | Not measured | 13.5% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text | 1419 | 1451 | DeepSeek V4 Pro 0423 |
| LMArena Text: instruction following | 1404 | 1445 | DeepSeek V4 Pro 0423 |
| LMArena Text: creative writing | 1403 | 1446 | DeepSeek V4 Pro 0423 |
| LMArena Text: English | 1429 | 1459 | DeepSeek V4 Pro 0423 |
| LMArena Text: non-English | 1408 | 1439 | DeepSeek V4 Pro 0423 |
| LMArena Text: Chinese | Not measured | 1481 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: German | Not measured | 1458 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Japanese | Not measured | 1446 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Korean | Not measured | 1409 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: French | Not measured | 1473 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Spanish | Not measured | 1457 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Russian | 1435 | 1453 | DeepSeek V4 Pro 0423 |
| LMArena Text: Polish | 1427 | 1461 | DeepSeek V4 Pro 0423 |
| LMArena Text: multi-turn | 1411 | 1468 | DeepSeek V4 Pro 0423 |
| LMArena Text: longer queries | 1422 | 1458 | DeepSeek V4 Pro 0423 |
| LMArena Text: writing and language | 1409 | 1447 | DeepSeek V4 Pro 0423 |
| LMArena Text: entertainment and media | 1391 | 1431 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | DeepSeek V4 Pro 0423 | 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 Terminus costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 Terminus costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 Terminus 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 | DeepSeek V4 Pro 0423 |
|---|---|---|
| Maker | DeepSeek | DeepSeek |
| Weights | Open weights | Open weights |
| Released | September 22, 2025 | April 24, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.3063 | $1.225 |
| Output $/Mtok | $1.0142 | $2.716 |
| Coding index | Not benchmarked | 38.7 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | $0.57 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 Terminus better than DeepSeek V4 Pro 0423 for coding?
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for output tokens 2.7x cheaper ($1.0142 vs $2.716 per million) and work measured by Kagi LLM Benchmark or LMArena Text: medicine and healthcare, where it leads.
Which is cheaper, DeepSeek V3.1 Terminus or DeepSeek V4 Pro 0423?
DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; DeepSeek V4 Pro 0423 costs $1.225 and $2.716. Cost per solved task is known for DeepSeek V4 Pro 0423 only.
Which has the bigger context window, DeepSeek V3.1 Terminus or DeepSeek V4 Pro 0423?
DeepSeek V4 Pro 0423, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.1 Terminus vs DeepSeek V4 Pro 0423 comparison based on?
34 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1 Terminus's coding index rests on 0 independent benchmarks and DeepSeek V4 Pro 0423's on 5. Where only one model has a result, the page says so instead of naming a winner.