Model comparison
Claude Opus 4.8 vs Kimi K2.7 Code
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 43.3 on the Noometry Index. Kimi K2.7 Code costs 5.8× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. Claude Opus 4.8 scores higher in 5 categories and Kimi K2.7 Code in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.8 leads 64.7 to 39.0.
- The biggest single-benchmark swing is GBAEval: 70.9% for Claude Opus 4.8 and 0.9% for Kimi K2.7 Code.
- Kimi K2.7 Code is cheaper at $0.95 / $4 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 262K.
- Kimi K2.7 Code has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.8 | Kimi K2.7 Code | |
|---|---|---|
| Provider | Anthropic | Moonshot AI |
| Noometry Index | 60.7 | 43.3 |
| Released | 2026-05-28 | 2026-06-12 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $5 | $0.95 |
| Output $ / M tokens | $25 | $4 |
| Results tracked | 65 | 19 |
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Category by category
Coding Claude Opus 4.8 leads
Claude Opus 4.8: 59.9 (#12), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| DeepSWE | 59% | 30.5% |
| FrontierCode | 46.5% | 30.1% |
| LMArena WebDev | 1556 | 1473 |
| SciCode | 53.5% | 47.5% |
| WeirdML | 82.9% | 54.1% |
| ALE-Bench | 1,564 | 886.23 |
| GSO | 47.1% | — |
| LMArena Coding | 1490 | — |
Agentic & Tool Use Claude Opus 4.8 leads
Claude Opus 4.8: 47.6 (#11), Kimi K2.7 Code: 24.0 (#122)
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | 48.9% | 37.6% |
| GBAEval | 70.9% | 0.9% |
| Vending-Bench 2 | 5,787 | 5,083 |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
Reasoning Claude Opus 4.8 leads
Claude Opus 4.8: 64.7 (#16), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| SimpleBench | 64.8% | 57.9% |
| CritPt | 20.9% | 10% |
| Chess Puzzles | 34% | 21% |
| Surface Evolver Bench | 87.5% | 48.8% |
| Epoch Capabilities Index | 158.21 | 149.97 |
| ARC-AGI-2 | 72.1% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| LMArena Hard Prompts | 1482 | — |
| Mystery Game Puzzles | 36% | — |
| DTBench | 94.9% | — |
| LMCA | 57.5% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 59.9 | — |
Math Claude Opus 4.8 leads
Claude Opus 4.8: 78.4 (#13), Kimi K2.7 Code: 52.9 (#48)
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | 80% | 54% |
| FrontierMath Tier 4 | 56.1% | 12.2% |
| OTIS Mock AIME 2024-2025 | 98.3% | 95.6% |
| MathArena Final-Answer Competitions | 91.8% | — |
| ProofBench | 69% | — |
| LMArena Math | 1487 | — |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Claude Opus 4.8 leads
Claude Opus 4.8: 61.3 (#29), Kimi K2.7 Code: 53.5 (#57)
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | 91% | 87.9% |
| SimpleQA Verified | 53% | 36.5% |
| LMArena Expert | 1502 | — |
Multimodal Not comparable
Claude Opus 4.8: 42.9 (#26), Kimi K2.7 Code: —
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
Multilingual Not comparable
Claude Opus 4.8: 55.2 (#33), Kimi K2.7 Code: —
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1450 | — |
| LMArena Chinese | 1507 | — |
| LMArena French | 1481 | — |
| LMArena German | 1472 | — |
| LMArena Japanese | 1440 | — |
| LMArena Korean | 1432 | — |
| LMArena Russian | 1474 | — |
| LMArena Spanish | 1466 | — |
Instruction Following Not comparable
Claude Opus 4.8: 77.4 (#24), Kimi K2.7 Code: —
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| LMArena Instruction Following | 1476 | — |
Long Context Not comparable
Claude Opus 4.8: 45.4 (#35), Kimi K2.7 Code: —
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| LMArena Longer Query | 1483 | — |
Writing & Preference Not comparable
Claude Opus 4.8: 72.0 (#16), Kimi K2.7 Code: —
| Benchmark | Claude Opus 4.8 | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1461 | — |
| LMArena Creative Writing | 1454 | — |
| EQ-Bench Creative Writing | 1840 | — |
| EQ-Bench 4 | 1281 | — |
| LMArena Multi-Turn | 1476 | — |
Frequently asked questions
Is Claude Opus 4.8 better than Kimi K2.7 Code?
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 43.3 on the Noometry Index. Kimi K2.7 Code costs 5.8× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.8 or Kimi K2.7 Code?
Kimi K2.7 Code is cheaper. It lists at $0.95 per million input tokens and $4 per million output tokens; Claude Opus 4.8 lists at $5 and $25.
Is Claude Opus 4.8 or Kimi K2.7 Code better for coding?
Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 42.9 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4.8 does, with 1M tokens against 262K.
How many benchmarks do Claude Opus 4.8 and Kimi K2.7 Code share?
19 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Kimi K2.7 Code has 19.