gpt-oss-120b vs Grok 4.20
Grok 4.20 leads gpt-oss-120b on the Artificial Analysis Intelligence Index, 25.7 to 11.6, and gpt-oss-120b costs 5.0x less per output token ($0.50 vs $2.50 per million). Updated October 21, 2026; 30 benchmarks have a result for both.
gpt-oss-120b or Grok 4.20: which to pick
Only Grok 4.20 has a coding score, 33.3 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 5.0x cheaper ($0.50 vs $2.50 per million) and a lower cost per solved task ($0.51 against $0.72).
- Shared results
- 30
- gpt-oss-120b only
- 51
- Grok 4.20 only
- 25
- 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 Grok 4.20 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Grok 4.20
Grok 4.20 leads, 25.7 against 11.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only gpt-oss-120b has a AA Agentic Index result, 3.7.
Directional only
Reasoning
GPQA Diamond
Grok 4.20
Grok 4.20 leads, 88.6% against 78.5%.
Same board, both measured
Math
AIME
Grok 4.20
Grok 4.20 leads, 96.5% against 92.6%.
Same board, both measured
Knowledge
MMLU Pro
Grok 4.20
Grok 4.20 leads, 86.3% against 79.2%.
Same board, both measured
Web design
Design Arena: websites
Grok 4.20
Grok 4.20 leads, 1229 against 968.
Same board, both measured
Long documents
Listed context window
Grok 4.20
Grok 4.20 takes 2M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
gpt-oss-120b $0.0003, Grok 4.20 $0.0025 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
gpt-oss-120b
gpt-oss-120b $0.51, Grok 4.20 $0.72.
Published attempt cost and pass rate
At a glance
- Coding index
- gpt-oss-120b not benchmarked, Grok 4.20 33.3 from 2 benchmarks.
- Widest category
- Web design, 31.5 points apart on average over 6 shared benchmarks.
- Widest single gap
- Terminal-Bench: gpt-oss-120b 18.7% against Grok 4.20 57.3%, 38.6 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.50 against Grok 4.20 $2.50 per million output tokens, 5.0x apart.
- Context window
- gpt-oss-120b takes 131K tokens, Grok 4.20 2M.
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 | gpt-oss-120b | Bars | Grok 4.20 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 1 | ||
| Knowledge | 0 | 6 | ||
| Web design | 0 | 6 | ||
| General | 0 | 4 | ||
| All shared boards | 0 | 30 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified | 26.0% | Not measured | Only gpt-oss-120b measured |
| AA Coding Index | 30.4 | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | 83.2% | 84.3% | Grok 4.20 |
| SWE-bench Verified (Vals AI) | 33.6% | 72.2% | Grok 4.20 |
| Vibe Code Bench (Vals AI) | Not measured | 4.1% | Only Grok 4.20 measured |
| Code migration (Vals AI) | Not measured | 0.3% | Only Grok 4.20 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 44.2% | Only Grok 4.20 measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | Not measured | Only gpt-oss-120b measured |
| SciCode | 34.0% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | 37.9% | Grok 4.20 |
| Terminal-Bench | 18.7% | 57.3% | Grok 4.20 |
| WeirdML | 48.2% | 52.3% | Grok 4.20 |
| ALE-Bench | 575.6 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: coding | 1379 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: software and IT | 1387 | Not measured | Only gpt-oss-120b measured |
| SciCode | 7.7% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | 25.7 | Grok 4.20 |
| Epoch Capabilities Index | 139.8 | 152.1 | Grok 4.20 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | Not measured | Only gpt-oss-120b measured |
| Design Arena: agents building web apps | Not measured | 1144 | Only Grok 4.20 measured |
| Design Arena: agents building full-stack apps | Not measured | 1054 | Only Grok 4.20 measured |
| Design Arena: agents building mobile apps | Not measured | 1090 | Only Grok 4.20 measured |
| Design Arena: agents building Android apps | Not measured | 1052 | Only Grok 4.20 measured |
| Design Arena: agents building Godot games | Not measured | 1089 | Only Grok 4.20 measured |
| Design Arena: HTML slides | Not measured | 1180 | Only Grok 4.20 measured |
| Finance Agent (Vals AI) | Not measured | 28.5% | Only Grok 4.20 measured |
| Tax Agent Bench (Vals AI) | Not measured | 7.0% | Only Grok 4.20 measured |
| Legal Research Bench (Vals AI) | Not measured | 13.9% | Only Grok 4.20 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 11.7% | Only Grok 4.20 measured |
| τ²-Bench Telecom | 65.8% | 93.0% | Grok 4.20 |
| APEX-Agents | 4.4% | Not measured | Only gpt-oss-120b measured |
| METR time horizons | 56.6% | Not measured | Only gpt-oss-120b measured |
| Vending-Bench 2 | -$22 | $4,663 | Grok 4.20 |
| BrowseComp-Plus | 67.0% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | 88.6% | Grok 4.20 |
| MMMU Pro (Vals AI) | Not measured | 83.5% | Only Grok 4.20 measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | 91.1% | Grok 4.20 |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | 34.5% | Grok 4.20 |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only gpt-oss-120b measured |
| ARC-AGI | Not measured | 89.5% | Only Grok 4.20 measured |
| ARC-AGI-2 | Not measured | 65.1% | Only Grok 4.20 measured |
| SimpleBench | 22.1% | Not measured | Only gpt-oss-120b measured |
| Mystery game puzzles | 2.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: hard prompts | 1364 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: expert | 1356 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: hard prompts in English | 1368 | Not measured | Only gpt-oss-120b measured |
| Kagi LLM Benchmark | 58.6% | 75.0% | Grok 4.20 |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| AIME | 92.6% | 96.5% | Grok 4.20 |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only gpt-oss-120b measured |
| MGSM (Vals AI) | 92.0% | Not measured | Only gpt-oss-120b measured |
| AA Math Index | 93.4 | Not measured | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | 93.4% | Not measured | Only gpt-oss-120b measured |
| OTIS Mock AIME | 88.9% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: math | 1389 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: mathematical work | 1386 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | 86.3% | Grok 4.20 |
| LegalBench (Vals AI) | 75.9% | 77.7% | Grok 4.20 |
| CaseLaw (Vals AI) | 48.8% | 54.4% | Grok 4.20 |
| CorpFin (Vals AI) | 58.2% | 63.7% | Grok 4.20 |
| TaxEval (Vals AI) | 71.6% | 74.1% | Grok 4.20 |
| MortgageTax (Vals AI) | Not measured | 45.4% | Only Grok 4.20 measured |
| MedQA (Vals AI) | 91.4% | 94.5% | Grok 4.20 |
| MedCode (Vals AI) | Not measured | 32.2% | Only Grok 4.20 measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: science | 1382 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: medicine and healthcare | 1388 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: legal and government | 1355 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: business and finance | 1359 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| Design Arena: websites | 968 | 1229 | Grok 4.20 |
| Design Arena: UI components | 927 | 1199 | Grok 4.20 |
| Design Arena: game dev | 992 | 1192 | Grok 4.20 |
| Design Arena: data viz | 987 | 1217 | Grok 4.20 |
| Design Arena: 3D | 901 | 1193 | Grok 4.20 |
| Design Arena: all code categories | 963 | 1221 | Grok 4.20 |
| Design Arena: SVG | Not measured | 1164 | Only Grok 4.20 measured |
| Design Arena: ASCII art | Not measured | 1174 | Only Grok 4.20 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-120b | Grok 4.20 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 38.2% | Only Grok 4.20 measured |
| MedScribe (Vals AI) | Not measured | 63.4% | Only Grok 4.20 measured |
| Vals Multimodal Index | Not measured | 39.1% | Only Grok 4.20 measured |
| IFBench | 69.0% | 81.2% | Grok 4.20 |
| Long context reasoning (AA-LCR) | 52.0% | 69.0% | Grok 4.20 |
| DTBench | 76.3% | 90.1% | Grok 4.20 |
| LMCA | 22.1% | 38.7% | Grok 4.20 |
| Fiction.LiveBench | 44.4% | Not measured | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | 77.1% | Not measured | Only gpt-oss-120b measured |
| CL-bench | Not measured | 22.2% | Only Grok 4.20 measured |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| CL-bench Life | Not measured | 11.9% | Only Grok 4.20 measured |
| LMArena Text | 1366 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: instruction following | 1318 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: creative writing | 1274 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: English | 1375 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: non-English | 1351 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Chinese | 1385 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: German | 1353 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Japanese | 1331 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Korean | 1282 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: French | 1370 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Spanish | 1389 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Russian | 1343 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Polish | 1353 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | 1340 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: longer queries | 1319 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: writing and language | 1306 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: entertainment and media | 1292 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | Grok 4.20 | 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 | OpenAI gpt-oss-120b | SpaceXAI Grok 4.20 |
|---|---|---|
| Maker | OpenAI | xAI |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | March 31, 2026 |
| Context window | 131K | 2M |
| Input $/Mtok | $0.10 | $1.25 |
| Output $/Mtok | $0.50 | $2.50 |
| Coding index | Not benchmarked | 33.3 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.51 | $0.72 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than Grok 4.20 for coding?
Only Grok 4.20 has a coding score, 33.3 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 5.0x cheaper ($0.50 vs $2.50 per million) and a lower cost per solved task ($0.51 against $0.72).
Which is cheaper, gpt-oss-120b or Grok 4.20?
gpt-oss-120b costs $0.10 per million input tokens and $0.50 per million output tokens; Grok 4.20 costs $1.25 and $2.50. Per solved SWE-bench Verified task, gpt-oss-120b costs $0.51 and Grok 4.20 $0.72.
Which has the bigger context window, gpt-oss-120b or Grok 4.20?
Grok 4.20, with 2M tokens against 131K.
How many benchmarks is the gpt-oss-120b vs Grok 4.20 comparison based on?
30 benchmarks have a result for both models as of October 21, 2026. gpt-oss-120b's coding index rests on 1 independent benchmark and Grok 4.20's on 2. Where only one model has a result, the page says so instead of naming a winner.