DeepSeek V4 Pro 0813 vs gpt-oss-120b
DeepSeek V4 Pro 0813 leads gpt-oss-120b on the Artificial Analysis Intelligence Index, 36.0 to 11.6, and gpt-oss-120b costs 4.0x less per output token ($0.50 vs $1.98 per million). Updated October 22, 2026; 48 benchmarks have a result for both.
DeepSeek V4 Pro 0813 or gpt-oss-120b: which to pick
Only DeepSeek V4 Pro 0813 has a coding score, 56.1 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding.
Pick gpt-oss-120b for output tokens 4.0x cheaper ($0.50 vs $1.98 per million).
- Shared results
- 48
- DeepSeek V4 Pro 0813 only
- 30
- gpt-oss-120b only
- 33
- 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 Pro 0813 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 36.0 against 11.6.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 41.3 against 3.7.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 92.4% against 78.5%.
Same board, both measured
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 87.0% against 79.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only gpt-oss-120b has a Design Arena: websites result, 967.
Directional only
General
Vals Index
No call
Only DeepSeek V4 Pro 0813 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
DeepSeek V4 Pro 0813 $0.0016, gpt-oss-120b $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.10, gpt-oss-120b $0.51.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Pro 0813 56.1 from 5 benchmarks, gpt-oss-120b not benchmarked.
- Widest category
- Agentic work, 40.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- SWE-bench Verified (Vals AI): DeepSeek V4 Pro 0813 96.4% against gpt-oss-120b 33.6%, 62.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0813 $1.98 against gpt-oss-120b $0.50 per million output tokens, 4.0x apart.
- Context window
- DeepSeek V4 Pro 0813 takes 1.05M tokens, gpt-oss-120b 131K.
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 Pro 0813 | Bars | gpt-oss-120b | Ties |
|---|---|---|---|---|
| Coding | 8 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 8 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 8 | 0 | ||
| General | 17 | 0 | ||
| All shared boards | 48 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index80
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 41.8% | Only gpt-oss-120b measured |
| SWE-bench Verified | Not measured | 26.0% | Only gpt-oss-120b measured |
| LMArena WebDev | 1582 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| AA Coding Index | 68.8 | 30.4 | DeepSeek V4 Pro 0813 |
| LiveCodeBench (Vals AI) | 87.5% | 83.2% | DeepSeek V4 Pro 0813 |
| SWE-bench Verified (Vals AI) | 96.4% | 33.6% | DeepSeek V4 Pro 0813 |
| Terminal-Bench 4 (Vals AI) | 14.1% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench (Vals AI) | 82.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Code migration (Vals AI) | 41.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| IOI (Vals AI) | 51.6% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench 1-100 (Vals AI) | 17.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SkillsBench (Vals AI) | 53.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| CyberBench (Vals AI) | 72.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 87.8% | Only gpt-oss-120b measured |
| SciCode | 51.0% | 34.0% | DeepSeek V4 Pro 0813 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 23.5% | Only gpt-oss-120b measured |
| Terminal-Bench | Not measured | 18.7% | Only gpt-oss-120b measured |
| FrontierCode | 28.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| WeirdML | 66.2% | 48.2% | DeepSeek V4 Pro 0813 |
| ALE-Bench | 1403.2 | 575.6 | DeepSeek V4 Pro 0813 |
| LMArena Text: coding | 1469 | 1379 | DeepSeek V4 Pro 0813 |
| LMArena Text: software and IT | 1462 | 1387 | DeepSeek V4 Pro 0813 |
| LMArena WebDev: React | 1588 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena WebDev: HTML | 1566 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SciCode | Not measured | 7.7% | Only gpt-oss-120b measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Intelligence Index | 36.0 | 11.6 | DeepSeek V4 Pro 0813 |
| Epoch Capabilities Index | 155.6 | 139.8 | DeepSeek V4 Pro 0813 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Agentic Index | 41.3 | 3.7 | DeepSeek V4 Pro 0813 |
| SREBench (Vals AI) | 1.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Finance Agent (Vals AI) | 50.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Tax Agent Bench (Vals AI) | 26.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Legal Research Bench (Vals AI) | 40.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Excel Modeling Benchmark (Vals AI) | 52.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| τ²-Bench Telecom | Not measured | 65.8% | Only gpt-oss-120b measured |
| APEX-Agents | 47.3% | 4.4% | DeepSeek V4 Pro 0813 |
| METR time horizons | Not measured | 56.6% | Only gpt-oss-120b measured |
| Vending-Bench 2 | Not measured | -$22 | Only gpt-oss-120b measured |
| BrowseComp-Plus | Not measured | 67.0% | Only gpt-oss-120b measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| GPQA Diamond | 92.4% | 78.5% | DeepSeek V4 Pro 0813 |
| GPQA Diamond (Artificial Analysis run) | 92.8% | 78.2% | DeepSeek V4 Pro 0813 |
| Humanity's Last Exam (Artificial Analysis run) | 41.0% | 19.6% | DeepSeek V4 Pro 0813 |
| GPQA Diamond (Epoch AI run) | 91.7% | 75.8% | DeepSeek V4 Pro 0813 |
| ARC-AGI | 90.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ARC-AGI-2 | 61.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SimpleBench | Not measured | 22.1% | Only gpt-oss-120b measured |
| Chess puzzles | 46.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Mystery game puzzles | 43.0% | 2.0% | DeepSeek V4 Pro 0813 |
| LMArena Text: hard prompts | 1458 | 1364 | DeepSeek V4 Pro 0813 |
| LMArena Text: expert | 1459 | 1356 | DeepSeek V4 Pro 0813 |
| LMArena Text: hard prompts in English | 1463 | 1368 | DeepSeek V4 Pro 0813 |
| Kagi LLM Benchmark | Not measured | 58.6% | Only gpt-oss-120b measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| AIME | Not measured | 92.6% | Only gpt-oss-120b measured |
| MATH 500 (Vals AI) | Not measured | 94.8% | Only gpt-oss-120b measured |
| MGSM (Vals AI) | Not measured | 92.0% | Only gpt-oss-120b measured |
| AA Math Index | Not measured | 93.4 | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 93.4% | Only gpt-oss-120b measured |
| OTIS Mock AIME | 98.6% | 88.9% | DeepSeek V4 Pro 0813 |
| FrontierMath, tiers 1 to 3 | 64.6% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ProofBench | 50.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: math | 1441 | 1389 | DeepSeek V4 Pro 0813 |
| LMArena Text: mathematical work | 1443 | 1386 | DeepSeek V4 Pro 0813 |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | 79.2% | DeepSeek V4 Pro 0813 |
| LegalBench (Vals AI) | 82.4% | 75.9% | DeepSeek V4 Pro 0813 |
| CaseLaw (Vals AI) | Not measured | 48.8% | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 65.4% | 58.2% | DeepSeek V4 Pro 0813 |
| TaxEval (Vals AI) | 73.1% | 71.6% | DeepSeek V4 Pro 0813 |
| MedQA (Vals AI) | Not measured | 91.4% | Only gpt-oss-120b measured |
| MedCode (Vals AI) | 42.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 80.8% | Only gpt-oss-120b measured |
| SimpleQA Verified | 52.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: science | 1457 | 1382 | DeepSeek V4 Pro 0813 |
| LMArena Text: medicine and healthcare | 1446 | 1388 | DeepSeek V4 Pro 0813 |
| LMArena Text: legal and government | 1459 | 1355 | DeepSeek V4 Pro 0813 |
| LMArena Text: business and finance | 1442 | 1359 | DeepSeek V4 Pro 0813 |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 967 | Only gpt-oss-120b measured |
| Design Arena: UI components | Not measured | 924 | Only gpt-oss-120b measured |
| Design Arena: game dev | Not measured | 992 | Only gpt-oss-120b measured |
| Design Arena: data viz | Not measured | 987 | Only gpt-oss-120b measured |
| Design Arena: 3D | Not measured | 901 | Only gpt-oss-120b measured |
| Design Arena: all code categories | Not measured | 962 | Only gpt-oss-120b measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | Leader |
|---|---|---|---|
| Vals Index | 53.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| MedScribe (Vals AI) | 80.2% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| IFBench | Not measured | 69.0% | Only gpt-oss-120b measured |
| Long context reasoning (AA-LCR) | 80.3% | 52.0% | DeepSeek V4 Pro 0813 |
| DTBench | 93.9% | 76.3% | DeepSeek V4 Pro 0813 |
| LMCA | 45.5% | 22.1% | DeepSeek V4 Pro 0813 |
| Fiction.LiveBench | Not measured | 44.4% | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | Not measured | 77.1% | Only gpt-oss-120b measured |
| Surface Evolver Bench | Not measured | 25.0% | Only gpt-oss-120b measured |
| LMArena Text | 1446 | 1366 | DeepSeek V4 Pro 0813 |
| LMArena Text: instruction following | 1448 | 1318 | DeepSeek V4 Pro 0813 |
| LMArena Text: creative writing | 1439 | 1274 | DeepSeek V4 Pro 0813 |
| LMArena Text: English | 1457 | 1375 | DeepSeek V4 Pro 0813 |
| LMArena Text: non-English | 1431 | 1351 | DeepSeek V4 Pro 0813 |
| LMArena Text: Chinese | 1481 | 1385 | DeepSeek V4 Pro 0813 |
| LMArena Text: German | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: Japanese | Not measured | 1331 | Only gpt-oss-120b measured |
| LMArena Text: Korean | 1449 | 1282 | DeepSeek V4 Pro 0813 |
| LMArena Text: French | 1446 | 1370 | DeepSeek V4 Pro 0813 |
| LMArena Text: Spanish | 1435 | 1389 | DeepSeek V4 Pro 0813 |
| LMArena Text: Russian | 1448 | 1343 | DeepSeek V4 Pro 0813 |
| LMArena Text: Polish | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | 1454 | 1340 | DeepSeek V4 Pro 0813 |
| LMArena Text: longer queries | 1458 | 1319 | DeepSeek V4 Pro 0813 |
| LMArena Text: writing and language | 1443 | 1306 | DeepSeek V4 Pro 0813 |
| LMArena Text: entertainment and media | 1424 | 1292 | DeepSeek V4 Pro 0813 |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | gpt-oss-120b | 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
gpt-oss-120b costs less
Repository review
50K input + 3K output tokens
gpt-oss-120b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-120b 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 Pro 0813 | OpenAI gpt-oss-120b |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | Open weights |
| Released | August 12, 2026 | August 5, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.66 | $0.10 |
| Output $/Mtok | $1.98 | $0.50 |
| Coding index | 56.1 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | $0.10 | $0.51 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0813 better than gpt-oss-120b for coding?
Only DeepSeek V4 Pro 0813 has a coding score, 56.1 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 4.0x cheaper ($0.50 vs $1.98 per million).
Which is cheaper, DeepSeek V4 Pro 0813 or gpt-oss-120b?
DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; gpt-oss-120b costs $0.10 and $0.50. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and gpt-oss-120b $0.51.
Which has the bigger context window, DeepSeek V4 Pro 0813 or gpt-oss-120b?
DeepSeek V4 Pro 0813, with 1.05M tokens against 131K.
How many benchmarks is the DeepSeek V4 Pro 0813 vs gpt-oss-120b comparison based on?
48 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 independent benchmarks and gpt-oss-120b's on 1. Where only one model has a result, the page says so instead of naming a winner.