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gpt-oss-120b vs Mistral Medium 3.1

gpt-oss-120b leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 11.6 to 9.2, and gpt-oss-120b costs 4.0x less per output token ($0.50 vs $2.00 per million). Updated October 21, 2026; 60 benchmarks have a result for both.

Replace gpt-oss-120b Replace Mistral Medium 3.1
gpt-oss-120bOpenAI
Coding
No data
Overall
50.0
Output $/M
$0.50
26
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
34
vs boards won of 60 shared

gpt-oss-120b or Mistral Medium 3.1: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick gpt-oss-120b for output tokens 4.0x cheaper ($0.50 vs $2.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model Agpt-oss-120bOpenAINot benchmarked1 independent benchmark$0.51 per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
60
gpt-oss-120b only
21
Mistral Medium 3.1 only
14
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.

At a glance

Coding index
gpt-oss-120b not benchmarked, Mistral Medium 3.1 not benchmarked.
Widest category
Math, 25.3 points apart on average over 7 shared benchmarks.
Widest single gap
AIME 2025 (Artificial Analysis run): gpt-oss-120b 93.4% against Mistral Medium 3.1 38.3%, 55.1 points apart on a 0 to 100 scale.
Output price
gpt-oss-120b $0.50 against Mistral Medium 3.1 $2.00 per million output tokens, 4.0x apart.
Context window
Both take 131K tokens.

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.

Boards won, where both have a result
Categorygpt-oss-120bBarsMistral Medium 3.1Ties
Coding62
Intelligence10
Agentic work20
Reasoning23
Math52
Knowledge64
Web design06
General417
All shared boards2634
CodingLike-for-likeSix of these boards feed the Vibe Coding Index62
Coding benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
Aider polyglot41.8%Not measuredOnly gpt-oss-120b measured
SWE-bench Verified26.0%Not measuredOnly gpt-oss-120b measured
AA Coding Index30.420.5gpt-oss-120b
LiveCodeBench (Vals AI)83.2%44.8%gpt-oss-120b
SWE-bench Verified (Vals AI)33.6%Not measuredOnly gpt-oss-120b measured
LiveCodeBench (Artificial Analysis run)87.8%40.6%gpt-oss-120b
SciCode34.0%32.4%gpt-oss-120b
Terminal-Bench Hard (Artificial Analysis run)23.5%10.6%gpt-oss-120b
Terminal-Bench18.7%Not measuredOnly gpt-oss-120b measured
WeirdML48.2%Not measuredOnly gpt-oss-120b measured
ALE-Bench575.6210.2gpt-oss-120b
LMArena Text: coding13791433Mistral Medium 3.1
LMArena Text: software and IT13871436Mistral Medium 3.1
SciCode7.7%Not measuredOnly 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 index10
Intelligence benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
AA Intelligence Index11.69.2gpt-oss-120b
Epoch Capabilities Index139.8Not measuredOnly gpt-oss-120b measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
AA Agentic Index3.71.9gpt-oss-120b
τ²-Bench Telecom65.8%40.6%gpt-oss-120b
APEX-Agents4.4%Not measuredOnly gpt-oss-120b measured
METR time horizons56.6%Not measuredOnly gpt-oss-120b measured
Vending-Bench 2-$22Not measuredOnly gpt-oss-120b measured
BrowseComp-Plus67.0%Not measuredOnly 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 index23
Reasoning benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
GPQA Diamond78.5%Not measuredOnly gpt-oss-120b measured
MMMU Pro (Vals AI)Not measured63.0%Only Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)78.2%58.8%gpt-oss-120b
Humanity's Last Exam (Artificial Analysis run)19.6%4.7%gpt-oss-120b
GPQA Diamond (Epoch AI run)75.8%Not measuredOnly gpt-oss-120b measured
SimpleBench22.1%Not measuredOnly gpt-oss-120b measured
Mystery game puzzles2.0%Not measuredOnly gpt-oss-120b measured
LMArena Text: hard prompts13641426Mistral Medium 3.1
LMArena Text: expert13561408Mistral Medium 3.1
LMArena Text: hard prompts in English13681435Mistral Medium 3.1
LMArena Vision: diagramsNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3.1 measured
Kagi LLM Benchmark58.6%Not measuredOnly 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 index52
Math benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
AIME92.6%42.3%gpt-oss-120b
MATH 500 (Vals AI)94.8%87.0%gpt-oss-120b
MGSM (Vals AI)92.0%90.9%gpt-oss-120b
AA Math Index93.438.3gpt-oss-120b
AIME 2025 (Artificial Analysis run)93.4%38.3%gpt-oss-120b
OTIS Mock AIME88.9%Not measuredOnly gpt-oss-120b measured
LMArena Text: math13891408Mistral Medium 3.1
LMArena Text: mathematical work13861412Mistral Medium 3.1
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index64
Knowledge benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
MMLU Pro79.2%75.3%gpt-oss-120b
LegalBench (Vals AI)75.9%62.0%gpt-oss-120b
CaseLaw (Vals AI)48.8%Not measuredOnly gpt-oss-120b measured
CorpFin (Vals AI)58.2%50.7%gpt-oss-120b
TaxEval (Vals AI)71.6%70.3%gpt-oss-120b
MortgageTax (Vals AI)Not measured36.5%Only Mistral Medium 3.1 measured
MedQA (Vals AI)91.4%78.2%gpt-oss-120b
MMLU Pro (Artificial Analysis run)80.8%68.3%gpt-oss-120b
LMArena Text: science13821444Mistral Medium 3.1
LMArena Text: medicine and healthcare13881449Mistral Medium 3.1
LMArena Text: legal and government13551439Mistral Medium 3.1
LMArena Text: business and finance13591418Mistral Medium 3.1
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
Design Arena: websites9681133Mistral Medium 3.1
Design Arena: UI components9271100Mistral Medium 3.1
Design Arena: game dev9921074Mistral Medium 3.1
Design Arena: data viz9871144Mistral Medium 3.1
Design Arena: 3D9011081Mistral Medium 3.1
Design Arena: all code categories9631120Mistral Medium 3.1
Design Arena: SVGNot measured993Only Mistral Medium 3.1 measured
Design Arena: ASCII artNot measured997Only Mistral Medium 3.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index417
General benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
IFBench69.0%39.8%gpt-oss-120b
Long context reasoning (AA-LCR)52.0%42.7%gpt-oss-120b
DTBench76.3%67.5%gpt-oss-120b
LMCA22.1%19.1%gpt-oss-120b
Fiction.LiveBench44.4%Not measuredOnly gpt-oss-120b measured
Creative writing (Lech Mazur)77.1%Not measuredOnly gpt-oss-120b measured
Surface Evolver Bench25.0%Not measuredOnly gpt-oss-120b measured
LMArena Text13661424Mistral Medium 3.1
LMArena Text: instruction following13181398Mistral Medium 3.1
LMArena Text: creative writing12741391Mistral Medium 3.1
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: English13751438Mistral Medium 3.1
LMArena Text: non-English13511408Mistral Medium 3.1
LMArena Text: Chinese13851447Mistral Medium 3.1
LMArena Text: German13531432Mistral Medium 3.1
LMArena Text: Japanese13311379Mistral Medium 3.1
LMArena Text: Korean12821380Mistral Medium 3.1
LMArena Text: French13701460Mistral Medium 3.1
LMArena Text: Spanish13891433Mistral Medium 3.1
LMArena Text: Russian13431411Mistral Medium 3.1
LMArena Text: Polish13531430Mistral Medium 3.1
LMArena Text: multi-turn13401418Mistral Medium 3.1
LMArena Text: longer queries13191406Mistral Medium 3.1
LMArena Text: writing and language13061395Mistral Medium 3.1
LMArena Text: entertainment and media12921390Mistral Medium 3.1
LMArena Vision: EnglishNot measured1179Only Mistral Medium 3.1 measured
LMArena Vision: ChineseNot measured1190Only Mistral Medium 3.1 measured
LMArena Vision: reading textNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: humorNot measured1168Only Mistral Medium 3.1 measured
LMArena Vision: captioningNot measured1145Only Mistral Medium 3.1 measured
LMArena Vision: recognizing thingsNot measured1147Only Mistral Medium 3.1 measured
LMArena Vision: creative writingNot measured1200Only Mistral Medium 3.1 measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for gpt-oss-120b and Mistral Medium 3.1
Benchmarkgpt-oss-120bMistral Medium 3.1Leader
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$0.0003Fits in one request
Mistral Medium 3.1$0.0014Fits in one request

gpt-oss-120b costs less

Repository review

50K input + 3K output tokens

gpt-oss-120b$0.0065Fits in one request
Mistral Medium 3.1$0.026Fits in one request

gpt-oss-120b costs less

Agent loop

200K input + 10K output tokens

gpt-oss-120b$0.025Exceeds the context window
Mistral Medium 3.1$0.100Exceeds the context window

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.

Specifications of gpt-oss-120b and Mistral Medium 3.1
SpecificationOpenAI gpt-oss-120bMistral Medium 3.1
MakerOpenAIMistral AI
WeightsOpen weightsNo public weights listed
ReleasedAugust 5, 2025August 13, 2025
Context window131K131K
Input $/Mtok$0.10$0.40
Output $/Mtok$0.50$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved task$0.51Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is gpt-oss-120b better than Mistral Medium 3.1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 4.0x cheaper ($0.50 vs $2.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, gpt-oss-120b or Mistral Medium 3.1?

gpt-oss-120b costs $0.10 per million input tokens and $0.50 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for gpt-oss-120b only.

Which has the bigger context window, gpt-oss-120b or Mistral Medium 3.1?

Neither: both take 131K tokens.

How many benchmarks is the gpt-oss-120b vs Mistral Medium 3.1 comparison based on?

60 benchmarks have a result for both models as of October 21, 2026. gpt-oss-120b's coding index rests on 1 independent benchmark and Mistral Medium 3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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