GPT-5 Mini vs Kimi K2 Thinking
Kimi K2 Thinking leads GPT-5 Mini on the Artificial Analysis Intelligence Index, 22.0 to 20.6, and GPT-5 Mini costs 1.3x less per output token ($2.00 vs $2.50 per million). Updated October 22, 2026; 27 benchmarks have a result for both.
GPT-5 Mini or Kimi K2 Thinking: which to pick
Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; Kimi K2 Thinking has none, so the two cannot be ranked on coding.
Pick Kimi K2 Thinking for work measured by SWE-bench Verified or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 27
- GPT-5 Mini only
- 74
- Kimi K2 Thinking only
- 3
- 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 GPT-5 Mini has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 Thinking
Kimi K2 Thinking leads, 22.0 against 20.6.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5 Mini
GPT-5 Mini leads, 80.3% against 78.5%.
Same board, both measured
Math
AIME
GPT-5 Mini
GPT-5 Mini leads, 91.5% against 85.4%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5 Mini
GPT-5 Mini leads, 82.2% against 81.1%.
Same board, both measured
Web design
Design Arena: websites
GPT-5 Mini
GPT-5 Mini leads, 1125 against 1113.
Same board, both measured
Long documents
Listed context window
GPT-5 Mini
GPT-5 Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Mini
GPT-5 Mini $0.0013, Kimi K2 Thinking $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5 Mini
GPT-5 Mini $0.08, Kimi K2 Thinking $0.61.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5 Mini 34.2 from 2 benchmarks, Kimi K2 Thinking not benchmarked.
- Widest category
- Agentic work, 21.9 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Vals AI): GPT-5 Mini 86.6% against Kimi K2 Thinking 63.1%, 23.5 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Mini $2.00 against Kimi K2 Thinking $2.50 per million output tokens, 1.3x apart.
- Context window
- GPT-5 Mini takes 400K tokens, Kimi K2 Thinking 262K.
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-5 Mini | Bars | Kimi K2 Thinking | Ties |
|---|---|---|---|---|
| Coding | 4 | 3 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 2 | ||
| Math | 2 | 2 | ||
| Knowledge | 5 | 2 | ||
| Web design | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index43
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SWE-bench Verified | 59.8% | 63.4% | Kimi K2 Thinking |
| SWE-bench Multilingual | 39.7% | Not measured | Only GPT-5 Mini measured |
| LiveCodeBench (Vals AI) | 86.6% | 63.1% | GPT-5 Mini |
| SWE-bench Verified (Vals AI) | 60.8% | 60.2% | GPT-5 Mini |
| Vibe Code Bench (Vals AI) | 14.2% | Not measured | Only GPT-5 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 83.8% | 85.3% | Kimi K2 Thinking |
| SciCode | 39.0% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 31.1% | GPT-5 Mini |
| Terminal-Bench | 34.8% | 35.7% | Kimi K2 Thinking |
| WeirdML | 52.7% | 42.8% | GPT-5 Mini |
| ALE-Bench | Not measured | 597.5 | Only Kimi K2 Thinking measured |
| LMArena Text: coding | 1406 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: software and IT | 1394 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.6 | 22.0 | Kimi K2 Thinking |
| Epoch Capabilities Index | 145.3 | 145.8 | Kimi K2 Thinking |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 71.1% | 93.0% | Kimi K2 Thinking |
| METR time horizons | Not measured | 59.2% | Only Kimi K2 Thinking measured |
| Vending-Bench 2 | -$31 | Not measured | Only GPT-5 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | 55.5% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | 78.5% | GPT-5 Mini |
| MMMU Pro (Vals AI) | 78.9% | Not measured | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 82.8% | 83.8% | Kimi K2 Thinking |
| Humanity's Last Exam (Artificial Analysis run) | 21.5% | 23.8% | Kimi K2 Thinking |
| GPQA Diamond (Epoch AI run) | 75.0% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI | 54.3% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI-2 | 4.4% | Not measured | Only GPT-5 Mini measured |
| Chess puzzles | 24.0% | Not measured | Only GPT-5 Mini measured |
| Mystery game puzzles | 10.0% | Not measured | Only GPT-5 Mini measured |
| VPCT | 40.2% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: expert | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts in English | 1383 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: diagrams | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: homework | 1210 | Not measured | Only GPT-5 Mini measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AIME | 91.5% | 85.4% | GPT-5 Mini |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only GPT-5 Mini measured |
| MGSM (Vals AI) | 92.6% | 90.2% | GPT-5 Mini |
| AA Math Index | 90.7 | 94.7 | Kimi K2 Thinking |
| AIME 2025 (Artificial Analysis run) | 90.7% | 94.7% | Kimi K2 Thinking |
| OTIS Mock AIME | 86.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | 46.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5 Mini measured |
| ProofBench | 9.0% | Not measured | Only GPT-5 Mini measured |
| MATH level 5 | 97.8% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: math | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: mathematical work | 1380 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index52
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| MMLU Pro | 82.2% | 81.1% | GPT-5 Mini |
| LegalBench (Vals AI) | 81.8% | 80.2% | GPT-5 Mini |
| CaseLaw (Vals AI) | 68.5% | 65.7% | GPT-5 Mini |
| CorpFin (Vals AI) | 60.2% | 60.6% | Kimi K2 Thinking |
| TaxEval (Vals AI) | 75.2% | 71.7% | GPT-5 Mini |
| MortgageTax (Vals AI) | 66.9% | Not measured | Only GPT-5 Mini measured |
| MedQA (Vals AI) | 96.1% | 92.6% | GPT-5 Mini |
| MedCode (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | 83.7% | 84.8% | Kimi K2 Thinking |
| SimpleQA Verified | 21.6% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: science | 1371 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: medicine and healthcare | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: legal and government | 1375 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: business and finance | 1358 | Not measured | Only GPT-5 Mini measured |
| FACTS Benchmark Suite | 38.6% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Design Arena: websites | 1125 | 1113 | GPT-5 Mini |
| Design Arena: UI components | 1103 | Not measured | Only GPT-5 Mini measured |
| Design Arena: game dev | 1129 | Not measured | Only GPT-5 Mini measured |
| Design Arena: data viz | 1131 | Not measured | Only GPT-5 Mini measured |
| Design Arena: 3D | 1036 | Not measured | Only GPT-5 Mini measured |
| Design Arena: all code categories | 1114 | Not measured | Only GPT-5 Mini measured |
| Design Arena: SVG | 1091 | Not measured | Only GPT-5 Mini measured |
| Design Arena: ASCII art | 1125 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | 80.6% | Not measured | Only GPT-5 Mini measured |
| IFBench | 75.4% | 68.1% | GPT-5 Mini |
| Long context reasoning (AA-LCR) | 72.3% | 72.0% | GPT-5 Mini |
| DTBench | 80.5% | Not measured | Only GPT-5 Mini measured |
| LMCA | 34.2% | Not measured | Only GPT-5 Mini measured |
| Fiction.LiveBench | 69.4% | Not measured | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | 83.1% | Not measured | Only GPT-5 Mini measured |
| CL-bench | Not measured | 17.6% | Only Kimi K2 Thinking measured |
| LMArena Text | 1373 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: instruction following | 1357 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: creative writing | 1325 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: English | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: non-English | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Chinese | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: German | 1366 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Japanese | 1341 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1308 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: French | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Spanish | 1354 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Russian | 1362 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Polish | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: longer queries | 1355 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: writing and language | 1344 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: entertainment and media | 1340 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: English | 1216 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | 1214 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: reading text | 1199 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: humor | 1205 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: captioning | 1217 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | 1181 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Mini | Kimi K2 Thinking | 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-5 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5 Mini 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-5 Mini | MoonshotAI Kimi K2 Thinking |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | August 7, 2025 | November 6, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.25 | $0.60 |
| Output $/Mtok | $2.00 | $2.50 |
| Coding index | 34.2 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.08 | $0.61 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Mini better than Kimi K2 Thinking for coding?
Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; Kimi K2 Thinking has none, so the two cannot be ranked on coding. Pick Kimi K2 Thinking for work measured by SWE-bench Verified or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, GPT-5 Mini or Kimi K2 Thinking?
GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Kimi K2 Thinking costs $0.60 and $2.50. Per solved SWE-bench Verified task, GPT-5 Mini costs $0.08 and Kimi K2 Thinking $0.61.
Which has the bigger context window, GPT-5 Mini or Kimi K2 Thinking?
GPT-5 Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5 Mini vs Kimi K2 Thinking comparison based on?
27 benchmarks have a result for both models as of October 22, 2026. GPT-5 Mini's coding index rests on 2 independent benchmarks and Kimi K2 Thinking's on 1. Where only one model has a result, the page says so instead of naming a winner.