DeepSeek V3 0324 vs gpt-oss-120b
gpt-oss-120b leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 11.6 to 9.7, and gpt-oss-120b costs 2.1x less per output token ($0.50 vs $1.07 per million). Updated October 22, 2026; 34 benchmarks have a result for both.
DeepSeek V3 0324 or gpt-oss-120b: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for a larger context window (164K against 131K tokens) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.
- Shared results
- 34
- DeepSeek V3 0324 only
- 1
- gpt-oss-120b only
- 47
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
gpt-oss-120b
gpt-oss-120b leads, 11.6 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
gpt-oss-120b
gpt-oss-120b leads, 3.7 against 0.8.
Same board, both measured
Reasoning
GPQA Diamond
gpt-oss-120b
gpt-oss-120b leads, 78.5% against 61.6%.
Same board, both measured
Math
AIME
gpt-oss-120b
gpt-oss-120b leads, 92.6% against 52.2%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V3 0324
DeepSeek V3 0324 leads, 79.5% 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
Long documents
Listed context window
DeepSeek V3 0324
DeepSeek V3 0324 takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
DeepSeek V3 0324 $0.0008, gpt-oss-120b $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, gpt-oss-120b not benchmarked.
- Widest category
- Math, 33.8 points apart on average over 6 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): DeepSeek V3 0324 41.0% against gpt-oss-120b 93.4%, 52.4 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against gpt-oss-120b $0.50 per million output tokens, 2.1x apart.
- Context window
- DeepSeek V3 0324 takes 164K 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 V3 0324 | Bars | gpt-oss-120b | Ties |
|---|---|---|---|---|
| Coding | 2 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 1 | 4 | ||
| Math | 0 | 6 | ||
| Knowledge | 3 | 3 | ||
| General | 1 | 5 | ||
| All shared boards | 7 | 27 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index25
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 41.8% | Only gpt-oss-120b measured |
| SWE-bench Verified | 42.0% | 26.0% | DeepSeek V3 0324 |
| AA Coding Index | 21.2 | 30.4 | gpt-oss-120b |
| LiveCodeBench (Vals AI) | 65.5% | 83.2% | gpt-oss-120b |
| SWE-bench Verified (Vals AI) | Not measured | 33.6% | Only gpt-oss-120b measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | 87.8% | gpt-oss-120b |
| SciCode | 39.0% | 34.0% | DeepSeek V3 0324 |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 23.5% | gpt-oss-120b |
| Terminal-Bench | Not measured | 18.7% | Only gpt-oss-120b measured |
| WeirdML | 36.1% | 48.2% | gpt-oss-120b |
| ALE-Bench | Not measured | 575.6 | Only gpt-oss-120b measured |
| LMArena Text: coding | Not measured | 1379 | Only gpt-oss-120b measured |
| LMArena Text: software and IT | Not measured | 1387 | Only gpt-oss-120b measured |
| SciCode | Not measured | 7.7% | Only gpt-oss-120b measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 11.6 | gpt-oss-120b |
| Epoch Capabilities Index | Not measured | 139.8 | Only gpt-oss-120b measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 3.7 | gpt-oss-120b |
| τ²-Bench Telecom | 47.1% | 65.8% | gpt-oss-120b |
| APEX-Agents | Not measured | 4.4% | Only gpt-oss-120b measured |
| METR time horizons | 49.6% | 56.6% | gpt-oss-120b |
| 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 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | 78.5% | gpt-oss-120b |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 78.2% | gpt-oss-120b |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 19.6% | gpt-oss-120b |
| GPQA Diamond (Epoch AI run) | 67.6% | 75.8% | gpt-oss-120b |
| SimpleBench | 27.2% | 22.1% | DeepSeek V3 0324 |
| Mystery game puzzles | Not measured | 2.0% | Only gpt-oss-120b measured |
| LMArena Text: hard prompts | Not measured | 1364 | Only gpt-oss-120b measured |
| LMArena Text: expert | Not measured | 1356 | Only gpt-oss-120b measured |
| LMArena Text: hard prompts in English | Not measured | 1368 | Only gpt-oss-120b measured |
| Kagi LLM Benchmark | Not measured | 58.6% | Only gpt-oss-120b measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| AIME | 52.2% | 92.6% | gpt-oss-120b |
| MATH 500 (Vals AI) | 88.6% | 94.8% | gpt-oss-120b |
| MGSM (Vals AI) | 91.7% | 92.0% | gpt-oss-120b |
| AA Math Index | 41.0 | 93.4 | gpt-oss-120b |
| AIME 2025 (Artificial Analysis run) | 41.0% | 93.4% | gpt-oss-120b |
| OTIS Mock AIME | 37.8% | 88.9% | gpt-oss-120b |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: math | Not measured | 1389 | Only gpt-oss-120b measured |
| LMArena Text: mathematical work | Not measured | 1386 | Only gpt-oss-120b measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | 79.2% | DeepSeek V3 0324 |
| LegalBench (Vals AI) | 77.7% | 75.9% | DeepSeek V3 0324 |
| CaseLaw (Vals AI) | Not measured | 48.8% | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 54.7% | 58.2% | gpt-oss-120b |
| TaxEval (Vals AI) | 71.1% | 71.6% | gpt-oss-120b |
| MedQA (Vals AI) | 82.0% | 91.4% | gpt-oss-120b |
| MMLU Pro (Artificial Analysis run) | 81.9% | 80.8% | DeepSeek V3 0324 |
| LMArena Text: science | Not measured | 1382 | Only gpt-oss-120b measured |
| LMArena Text: medicine and healthcare | Not measured | 1388 | Only gpt-oss-120b measured |
| LMArena Text: legal and government | Not measured | 1355 | Only gpt-oss-120b measured |
| LMArena Text: business and finance | Not measured | 1359 | Only gpt-oss-120b measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V3 0324 | 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 index15
| Benchmark | DeepSeek V3 0324 | gpt-oss-120b | Leader |
|---|---|---|---|
| IFBench | 41.0% | 69.0% | gpt-oss-120b |
| Long context reasoning (AA-LCR) | 40.7% | 52.0% | gpt-oss-120b |
| DTBench | 64.8% | 76.3% | gpt-oss-120b |
| LMCA | 15.5% | 22.1% | gpt-oss-120b |
| Fiction.LiveBench | 50.0% | 44.4% | DeepSeek V3 0324 |
| Creative writing (Lech Mazur) | 77.0% | 77.1% | gpt-oss-120b |
| Surface Evolver Bench | Not measured | 25.0% | Only gpt-oss-120b measured |
| LMArena Text | Not measured | 1366 | Only gpt-oss-120b measured |
| LMArena Text: instruction following | Not measured | 1318 | Only gpt-oss-120b measured |
| LMArena Text: creative writing | Not measured | 1274 | Only gpt-oss-120b measured |
| LMArena Text: English | Not measured | 1375 | Only gpt-oss-120b measured |
| LMArena Text: non-English | Not measured | 1351 | Only gpt-oss-120b measured |
| LMArena Text: Chinese | Not measured | 1385 | Only gpt-oss-120b measured |
| 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 | Not measured | 1282 | Only gpt-oss-120b measured |
| LMArena Text: French | Not measured | 1370 | Only gpt-oss-120b measured |
| LMArena Text: Spanish | Not measured | 1389 | Only gpt-oss-120b measured |
| LMArena Text: Russian | Not measured | 1343 | Only gpt-oss-120b measured |
| LMArena Text: Polish | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | Not measured | 1340 | Only gpt-oss-120b measured |
| LMArena Text: longer queries | Not measured | 1319 | Only gpt-oss-120b measured |
| LMArena Text: writing and language | Not measured | 1306 | Only gpt-oss-120b measured |
| LMArena Text: entertainment and media | Not measured | 1292 | Only gpt-oss-120b measured |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | 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 V3 0324 | OpenAI gpt-oss-120b |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | Open weights |
| Released | March 24, 2025 | August 5, 2025 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.27 | $0.10 |
| Output $/Mtok | $1.07 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.51 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than gpt-oss-120b for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for a larger context window (164K against 131K tokens) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, DeepSeek V3 0324 or gpt-oss-120b?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; gpt-oss-120b costs $0.10 and $0.50. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, DeepSeek V3 0324 or gpt-oss-120b?
DeepSeek V3 0324, with 164K tokens against 131K.
How many benchmarks is the DeepSeek V3 0324 vs gpt-oss-120b comparison based on?
34 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324's coding index rests on 0 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.