Model comparison
Claude Mythos 5 vs Kimi K2
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Mythos 5 #1 (Supported); Kimi K2 #189 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Mythos 5 and Kimi K2 share 0 comparable benchmark results. 1 of 8 categories are comparable. 15 results are unique to Claude Mythos 5; 14 to Kimi K2.
Updated July 23, 2026- Shared results
- 0
- Claude Mythos 5 only
- 15
- Kimi K2 only
- 14
- Comparable categories
- 1 / 8
Pick Claude Mythos 5 if you want the stronger benchmark profile. Kimi K2 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Mythos 5 is clearly ahead on the BenchAlign aggregate, 83.93 to 27.19. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Mythos 5's sharpest advantage is in mathematics, where it averages 97.6 against 16.1.
Claude Mythos 5 is also the more expensive model on tokens at $10.00 input / $50.00 output per 1M tokens, versus $0.60 input / $2.50 output per 1M tokens for Kimi K2. That is roughly 20.0x on output cost alone. Claude Mythos 5 is the reasoning model in the pair, while Kimi K2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Mythos 5 gives you the larger context window at 1M+, compared with 128K for Kimi K2.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Mythos 5 | Kimi K2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Mythos 5$10 input / $50 output | Kimi K2$0.6 input / $2.5 output | Kimi K2 has the lower combined listed price. |
| Generation speedtokens per second | Claude Mythos 5Not available | Kimi K243 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Mythos 5Not available | Kimi K21.51 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Mythos 51M+ | Kimi K2128K | Claude Mythos 5 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2 | Result |
|---|---|---|---|
| GPQASource | 94.1% | — | Not comparable |
| HLESource | 64.5% | — | Not comparable |
| HLE w/o toolsSource | 59% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 19.4% | Not comparable |
| AA-GPQA DiamondSource | — | 76.6% | Not comparable |
| AA-HLESource | — | 7.0% | Not comparable |
| AA-Omniscience IndexSource | — | -27.5% | Not comparable |
| AA-Omniscience AccuracySource | — | 26.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 74.2% | Not comparable |
MathClaude Mythos 5 wins3 benchmarks
Multilingual1 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2 | Result |
|---|---|---|---|
| SWE MultilingualSource | 92.2% | — | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 41.5% | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude Mythos 5 or Kimi K2?
Claude Mythos 5 is ahead on BenchLM's BenchAlign leaderboard, 83.93 to 27.19.
Which is better for math, Claude Mythos 5 or Kimi K2?
Claude Mythos 5 has the edge for math in this comparison, averaging 97.6 versus 16.1. Kimi K2 stays close enough that the answer can still flip depending on your workload.
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