Model comparison
Claude Mythos 5 vs Kimi K2.5
Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Mythos 5 #1 (Supported); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Mythos 5 and Kimi K2.5 share 6 comparable benchmark results. 5 of 8 categories are comparable. 9 results are unique to Claude Mythos 5; 57 to Kimi K2.5.
Updated July 23, 2026- Shared results
- 6
- Claude Mythos 5 only
- 9
- Kimi K2.5 only
- 57
- Comparable categories
- 5 / 8
Pick Claude Mythos 5 if you want the stronger benchmark profile. Kimi K2.5 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 6 shared benchmark results across 3 evidence categories; 5 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 59.66. 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 60.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 88% to 50.8%.
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 / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 16.7x on output cost alone. Claude Mythos 5 is the reasoning model in the pair, while Kimi K2.5 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 256K for Kimi K2.5.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Mythos 5 | Δ | Kimi K2.5 |
|---|---|---|---|
| Math | Claude Mythos 597.6 | Margin← 37.0 | Kimi K2.560.6 |
| Agentic | Claude Mythos 587.0 | Margin← 32.0 | Kimi K2.555.0 |
| Coding | Claude Mythos 589.7 | Margin← 30.3 | Kimi K2.559.4 |
| Multimodal | Claude Mythos 593.5 | Margin← 15.0 | Kimi K2.578.5 |
| Knowledge | Claude Mythos 568.5 | Margin← 11.6 | Kimi K2.556.9 |
| Reasoning | Claude Mythos 5Not measured | MarginNo overlap | Kimi K2.561.0 |
| Multilingual | Claude Mythos 5Not measured | MarginNo overlap | Kimi K2.582.3 |
| Inst. Following | Claude Mythos 5Not measured | MarginNo overlap | Kimi K2.593.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 88%B 50.8%Winner: Claude Mythos 5Δ 37.2Terminal-Bench 2.0: Claude Mythos 5 scored 88%; Kimi K2.5 scored 50.8%. Claude Mythos 5 wins this benchmark. - Source ↗
HLE
KnowledgeA 64.5%B 30.1%Winner: Claude Mythos 5Δ 34.4HLE: Claude Mythos 5 scored 64.5%; Kimi K2.5 scored 30.1%. Claude Mythos 5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 80.3%B 50.7%Winner: Claude Mythos 5Δ 29.6SWE-bench Pro: Claude Mythos 5 scored 80.3%; Kimi K2.5 scored 50.7%. Claude Mythos 5 wins this benchmark. - Source ↗
BrowseComp
AgenticA 88%B 60.6%Winner: Claude Mythos 5Δ 27.4BrowseComp: Claude Mythos 5 scored 88%; Kimi K2.5 scored 60.6%. Claude Mythos 5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 95.5%B 76.8%Winner: Claude Mythos 5Δ 18.7SWE-bench Verified: Claude Mythos 5 scored 95.5%; Kimi K2.5 scored 76.8%. Claude Mythos 5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Mythos 5 | Kimi K2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Mythos 5$10 input / $50 output | Kimi K2.5$0.6 input / $3 output | Kimi K2.5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Mythos 5Not available | Kimi K2.545 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Mythos 5Not available | Kimi K2.52.38 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Mythos 51M+ | Kimi K2.5256K | Claude Mythos 5 lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Mythos 5 wins21 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 88% | 50.8% | Claude Mythos 5 leads |
| OSWorld-VerifiedSource | 85% | — | Not comparable |
| BrowseCompSource | 88% | 60.6% | Claude Mythos 5 leads |
| ExploitGymSource | 17.5% | — | Not comparable |
| Claw-EvalSource | — | 52.3% | Not comparable |
| QwenClawBenchSource | — | 54.3% | Not comparable |
| τ³-bench resultsSource | — | 65.7% | Not comparable |
| DeepSearchQASource | — | 77.1% | Not comparable |
| DeepPlanningSource | — | 14.4% | Not comparable |
| ToolathlonSource | — | 27.8% | Not comparable |
| MCP AtlasSource | — | 29.5% | Not comparable |
| MCP-TasksSource | — | 59.1% | Not comparable |
| WideResearchSource | — | 72.7% | Not comparable |
| τ²-bench resultsSource | — | 95.9% | Not comparable |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| Gert LabsSource | — | 45.88% | Not comparable |
| ResearchClawBenchSource | — | 14.0% | Not comparable |
| JobBenchSource | — | 8.7% | Not comparable |
| AA Agentic IndexSource | — | 21.7% | Not comparable |
| GDPval-AASource | — | 25.4% | Not comparable |
| GDPval-AASource | — | 1009 | Not comparable |
CodingClaude Mythos 5 wins11 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2.5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 95.5% | 76.8% | Claude Mythos 5 leads |
| SWE-bench ProSource | 80.3% | 50.7% | Claude Mythos 5 leads |
| Terminal-Bench 2.0Source | 88.0% | — | Not comparable |
| SWE-bench Verified*Source | — | 70.8% | Not comparable |
| LiveCodeBench v6Source | — | 85.0% | Not comparable |
| SWE MultilingualSource | — | 73% | Not comparable |
| SWE-RebenchSource | — | 58.5% | Not comparable |
| React Native EvalsSource | — | 77.2% | Not comparable |
| SciCodeSource | — | 48.7% | Not comparable |
| AA-SciCodeSource | — | 49.0% | Not comparable |
| AA Coding IndexSource | — | 46.8% | Not comparable |
Reasoning3 benchmarks
KnowledgeClaude Mythos 5 wins13 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2.5 | Result |
|---|---|---|---|
| GPQASource | 94.1% | 87.6% | Claude Mythos 5 leads |
| HLESource | 64.5% | 30.1% | Claude Mythos 5 leads |
| HLE w/o toolsSource | 59% | — | Not comparable |
| GPQA-DSource | — | 87.6% | Not comparable |
| SuperGPQASource | — | 69.2% | Not comparable |
| MMLU-ProSource | — | 87.1% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 87.1% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 35.4% | Not comparable |
| AA-GPQA DiamondSource | — | 87.9% | Not comparable |
| AA-HLESource | — | 29.4% | Not comparable |
| AA-Omniscience IndexSource | — | -8.1% | Not comparable |
| AA-Omniscience AccuracySource | — | 34.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 64.6% | Not comparable |
MathClaude Mythos 5 wins10 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2.5 | Result |
|---|---|---|---|
| USAMO 2026Source | 97.6% | — | Not comparable |
| AIME 2025Source | — | 96.1% | Not comparable |
| AIME26Source | — | 95.8% | Not comparable |
| AIME25 (Arcee)Source | — | 96.3% | Not comparable |
| HMMT Feb 2025Source | — | 95.4% | Not comparable |
| HMMT Nov 2025Source | — | 91.1% | Not comparable |
| HMMT Feb 2026Source | — | 87.1% | Not comparable |
| MMAnswerBenchSource | — | 81.8% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 27.900% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 4.200% | Not comparable |
Multilingual3 benchmarks
MultimodalClaude Mythos 5 wins9 benchmarks
| Benchmark | Claude Mythos 5 | Kimi K2.5 | Result |
|---|---|---|---|
| SWE-bench MultimodalSource | 54.9% | — | Not comparable |
| CharXivSource | 93.5% | — | Not comparable |
| CharXiv w/o toolsSource | 88.9% | — | Not comparable |
| MMMU-ProSource | — | 78.5% | Not comparable |
| Video-MMESource | — | 87.4% | Not comparable |
| MMVUSource | — | 80.4% | Not comparable |
| VideoMMMUSource | — | 86.6% | Not comparable |
| AA-MMMU-ProSource | — | 75.4% | Not comparable |
| Design Arena WebsiteSource | — | 1279 | Not comparable |
Frequently Asked Questions (6)
Which is better, Claude Mythos 5 or Kimi K2.5?
Claude Mythos 5 is ahead on BenchLM's BenchAlign leaderboard, 83.93 to 59.66. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 88% and 50.8%.
Which is better for knowledge tasks, Claude Mythos 5 or Kimi K2.5?
Claude Mythos 5 has the edge for knowledge tasks in this comparison, averaging 68.5 versus 56.9. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Mythos 5 or Kimi K2.5?
Claude Mythos 5 has the edge for coding in this comparison, averaging 89.7 versus 59.4. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for math, Claude Mythos 5 or Kimi K2.5?
Claude Mythos 5 has the edge for math in this comparison, averaging 97.6 versus 60.6. Kimi K2.5 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Claude Mythos 5 or Kimi K2.5?
Claude Mythos 5 has the edge for agentic tasks in this comparison, averaging 87 versus 55. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Claude Mythos 5 or Kimi K2.5?
Claude Mythos 5 has the edge for multimodal and grounded tasks in this comparison, averaging 93.5 versus 78.5. Kimi K2.5 stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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