Model comparison
Claude Haiku 4.5 vs Kimi K2.6
Kimi K2.6 is the stronger model overall, scoring 47.5 to 39.3 on the Noometry Index.
Last verified . 38 shared benchmarks.
Summary
- They share 38 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 1 category and Kimi K2.6 in 9 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.6 leads 39.6 to 15.1.
- The biggest single-benchmark swing is NYT Connections (extended): 14.3% for Claude Haiku 4.5 and 87.2% for Kimi K2.6.
- Kimi K2.6 is cheaper at $0.95 / $4 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- Kimi K2.6 accepts more context: 262K tokens versus 200K.
- Kimi K2.6 has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Kimi K2.6 | |
|---|---|---|
| Provider | Anthropic | Moonshot AI |
| Noometry Index | 39.3 | 47.5 |
| Released | 2025-10-15 | 2026-04-20 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 64K | 262K |
| Input $ / M tokens | $1 | $0.95 |
| Output $ / M tokens | $5 | $4 |
| Results tracked | 53 | 51 |
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Category by category
Coding Kimi K2.6 leads
Claude Haiku 4.5: 43.9 (#71), Kimi K2.6: 50.5 (#41)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| LMArena WebDev | 1330 | 1509 |
| SciCode | 43.3% | 53.5% |
| WeirdML | 45.4% | 55.9% |
| LMArena Coding | 1454 | 1488 |
| ALE-Bench | 653.48 | 1,093 |
| SWE-bench Verified | — | 76.7% |
| SWE-bench Verified (bash only) | 66.6% | — |
| SWE-bench Multilingual | 64.7% | — |
Agentic & Tool Use Claude Haiku 4.5 leads
Claude Haiku 4.5: 33.5 (#50), Kimi K2.6: 21.8 (#128)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| ExploitBench | 13.7% | 18.4% |
| Vending-Bench 2 | 458.89 | 6,205 |
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| OSWorld 2.0 | — | 4.6% |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| GBAEval | — | 0.9% |
| GDP.pdf | — | 12% |
Reasoning Kimi K2.6 leads
Claude Haiku 4.5: 15.1 (#310), Kimi K2.6: 39.6 (#51)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| NYT Connections (extended) | 14.3% | 87.2% |
| CritPt | 0% | 8% |
| Chess Puzzles | 8% | 26% |
| LMArena Hard Prompts | 1420 | 1470 |
| DTBench | 73.6% | 90.9% |
| LMCA | 30.9% | 37.3% |
| Epoch Capabilities Index | 142.42 | 151.03 |
| ARC-AGI-2 | 4% | — |
| ARC-AGI-1 | 47.7% | — |
| EBR-Bench | — | 2.4% |
| Mystery Game Puzzles | — | 18% |
| ForecastBench | 61.4 | — |
Math Kimi K2.6 leads
Claude Haiku 4.5: 43.0 (#69), Kimi K2.6: 56.8 (#34)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 96.1% |
| LMArena Math | 1395 | 1475 |
| FrontierMath (Feb 2025 set) | 5.9% | 39% |
| FrontierMath Tier 4 (v1) | 2.1% | 14.6% |
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 25.6% |
| MathArena Final-Answer Competitions | — | 72.9% |
| ProofBench | — | 16% |
| Omni-MATH | 56.1% | — |
| MATH Level 5 | 96.4% | — |
Knowledge Kimi K2.6 leads
Claude Haiku 4.5: 37.6 (#146), Kimi K2.6: 53.9 (#48)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| GPQA Diamond | 71.2% | 90.8% |
| SimpleQA Verified | 13.2% | 34.9% |
| Vectara Hallucination Rate | 9.8% | 10.8% |
| LMArena Expert | 1443 | 1491 |
| MMLU-Pro | 77.7% | — |
| GPQA (HELM) | 60.5% | — |
Multimodal Kimi K2.6 leads
Claude Haiku 4.5: 27.0 (#111), Kimi K2.6: 31.8 (#95)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| Blueprint-Bench 2 | 0% | 3.9% |
| LMArena Document | 1420 | 1451 |
| LMArena Vision | — | 1282 |
| Furniture Assembly | — | 21.7% |
Multilingual Kimi K2.6 leads
Claude Haiku 4.5: 50.1 (#124), Kimi K2.6: 55.1 (#35)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| LMArena Non-English | 1376 | 1446 |
| LMArena Chinese | 1415 | 1521 |
| LMArena French | 1408 | 1471 |
| LMArena German | 1377 | 1449 |
| LMArena Japanese | 1339 | 1442 |
| LMArena Korean | 1346 | 1428 |
| LMArena Russian | 1380 | 1446 |
| LMArena Spanish | 1420 | 1463 |
Instruction Following Kimi K2.6 leads
Claude Haiku 4.5: 71.6 (#144), Kimi K2.6: 76.5 (#40)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| LMArena Instruction Following | 1414 | 1451 |
| IFEval | 80.1% | — |
Long Context Kimi K2.6 leads
Claude Haiku 4.5: 43.6 (#86), Kimi K2.6: 44.9 (#50)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| LMArena Longer Query | 1427 | 1468 |
Writing & Preference Kimi K2.6 leads
Claude Haiku 4.5: 58.1 (#119), Kimi K2.6: 68.7 (#25)
| Benchmark | Claude Haiku 4.5 | Kimi K2.6 |
|---|---|---|
| LMArena Text | 1396 | 1455 |
| LMArena Creative Writing | 1371 | 1434 |
| EQ-Bench 4 | 1064 | 1202 |
| LMArena Multi-Turn | 1409 | 1453 |
| EQ-Bench Creative Writing | — | 1725 |
| WildBench | 83.9% | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Kimi K2.6?
Kimi K2.6 is the stronger model overall, scoring 47.5 to 39.3 on the Noometry Index.
Which is cheaper, Claude Haiku 4.5 or Kimi K2.6?
Kimi K2.6 is cheaper. It lists at $0.95 per million input tokens and $4 per million output tokens; Claude Haiku 4.5 lists at $1 and $5.
Is Claude Haiku 4.5 or Kimi K2.6 better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.5 versus 43.9 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.6 does, with 262K tokens against 200K.
How many benchmarks do Claude Haiku 4.5 and Kimi K2.6 share?
38 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Kimi K2.6 has 51.