Model comparison
Kimi K2.5 vs LFM2.5-8B-A1B
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Kimi K2.5 #22; LFM2.5-8B-A1B unranked
BenchAlign evidence: Kimi K2.5 supported; LFM2.5-8B-A1B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 and LFM2.5-8B-A1B share 15 comparable benchmark results. 2 of 8 categories are comparable. 49 results are unique to Kimi K2.5; 3 to LFM2.5-8B-A1B.
Updated July 16, 2026- Shared results
- 15
- Kimi K2.5 only
- 49
- LFM2.5-8B-A1B only
- 3
- Comparable categories
- 2 / 8
Pick Kimi K2.5 if you want the stronger benchmark profile. LFM2.5-8B-A1B only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Kimi K2.5 is clearly ahead on the provisional aggregate, 61 to 37. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5's sharpest advantage is in instruction following, where it averages 93.9 against 68.8. The single biggest benchmark swing on the page is AIME26, 95.8% to 50.0%.
Kimi K2.5 is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-8B-A1B. That is roughly Infinityx on output cost alone. LFM2.5-8B-A1B 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. Kimi K2.5 gives you the larger context window at 256K, compared with 128K for LFM2.5-8B-A1B.
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 | Kimi K2.5 | Δ | LFM2.5-8B-A1B |
|---|---|---|---|
| Inst. Following | Kimi K2.593.9 | Margin← 25.1 | LFM2.5-8B-A1B68.8 |
| Math | Kimi K2.560.6 | Margin← 10.6 | LFM2.5-8B-A1B50.0 |
| Agentic | Kimi K2.555.0 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
| Coding | Kimi K2.559.4 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
| Reasoning | Kimi K2.561.0 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
| Knowledge | Kimi K2.557.2 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
| Multilingual | Kimi K2.582.3 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
| Multimodal | Kimi K2.578.5 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
AIME26
MathA 95.8%B 50.0%Winner: Kimi K2.5Δ 45.8AIME26: Kimi K2.5 scored 95.8%; LFM2.5-8B-A1B scored 50.0%. Kimi K2.5 wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 93.9%B 91.8%Winner: Kimi K2.5Δ 2.1IFEval: Kimi K2.5 scored 93.9%; LFM2.5-8B-A1B scored 91.8%. Kimi K2.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.5 | LFM2.5-8B-A1B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5$0.6 input / $3 output | LFM2.5-8B-A1B$0 input / $0 output | LFM2.5-8B-A1B has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.545 tok/s | LFM2.5-8B-A1BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.52.38 s | LFM2.5-8B-A1BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5256K | LFM2.5-8B-A1B128K | Kimi K2.5 lists the larger context window. |
Benchmark Deep Dive
Agentic20 benchmarks
| Benchmark | Kimi K2.5 | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | — | Not comparable |
| BrowseCompSource | 60.6% | — | 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% | 16.1% | Kimi K2.5 leads |
| 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 |
| BFCL v4Source | — | 49.7% | Not comparable |
Coding11 benchmarks
| Benchmark | Kimi K2.5 | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 76.8% | — | Not comparable |
| SWE-bench Verified*Source | 70.8% | — | Not comparable |
| LiveCodeBench v6Source | 85.0% | — | Not comparable |
| SWE-bench ProSource | 50.7% | — | 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 |
| Terminal-Bench HardSource | 34.8% | 4.5% | Kimi K2.5 leads |
| AA-SciCodeSource | 49.0% | 7.8% | Kimi K2.5 leads |
| AA Coding IndexSource | 46.8% | — | Not comparable |
Reasoning3 benchmarks
Knowledge12 benchmarks
| Benchmark | Kimi K2.5 | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| GPQASource | 87.6% | — | 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 |
| HLESource | 30.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.4% | 8.3% | Kimi K2.5 leads |
| AA-GPQA DiamondSource | 87.9% | 51.3% | Kimi K2.5 leads |
| AA-HLESource | 29.4% | 6.9% | Kimi K2.5 leads |
| AA-Omniscience IndexSource | -8.1% | -33.3% | Kimi K2.5 leads |
| AA-Omniscience AccuracySource | 34.3% | 9.4% | Kimi K2.5 leads |
| AA-Omniscience Hallucination RateSource | 64.6% | 47.0% | LFM2.5-8B-A1B leads |
MathKimi K2.5 wins10 benchmarks
| Benchmark | Kimi K2.5 | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| AIME 2025Source | 96.1% | 42.5% | Kimi K2.5 leads |
| AIME26Source | 95.8% | 50.0% | Kimi K2.5 leads |
| 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 |
| MATH-500Source | — | 88.8% | Not comparable |
Multilingual2 benchmarks
Multimodal6 benchmarks
Frequently Asked Questions (3)
Which is better, Kimi K2.5 or LFM2.5-8B-A1B?
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 61 to 37. The biggest single separator in this matchup is AIME26, where the scores are 95.8% and 50.0%.
Which is better for math, Kimi K2.5 or LFM2.5-8B-A1B?
Kimi K2.5 has the edge for math in this comparison, averaging 60.6 versus 50. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
Which is better for instruction following, Kimi K2.5 or LFM2.5-8B-A1B?
Kimi K2.5 has the edge for instruction following in this comparison, averaging 93.9 versus 68.8. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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