Model comparison
Kimi K2.6 vs LFM2.5-VL-1.6B-Extract
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.6 #74 (Estimated); LFM2.5-VL-1.6B-Extract unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.6 and LFM2.5-VL-1.6B-Extract share 12 comparable benchmark results. 0 of 8 categories are comparable. 39 results are unique to Kimi K2.6; 3 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 12
- Kimi K2.6 only
- 39
- LFM2.5-VL-1.6B-Extract only
- 3
- Comparable categories
- 0 / 8
Benchmark data for Kimi K2.6 and LFM2.5-VL-1.6B-Extract is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Kimi K2.6 has the larger context window at 256K, compared with 128K for LFM2.5-VL-1.6B-Extract.
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 K2.6 | Δ | LFM2.5-VL-1.6B-Extract |
|---|---|---|---|
| Agentic | Kimi K2.673.5 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Coding | Kimi K2.664.4 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Knowledge | Kimi K2.642.2 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Math | Kimi K2.667.1 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Multimodal | Kimi K2.679.8 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.6 | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.6$0.95 input / $4 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Kimi K2.6Not available | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.6Not available | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.6256K | LFM2.5-VL-1.6B-Extract128K | Kimi K2.6 lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Kimi K2.6 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 66.7% | — | Not comparable |
| BrowseCompSource | 83.2% | — | Not comparable |
| OSWorld-VerifiedSource | 73.1% | — | Not comparable |
| ToolathlonSource | 50% | — | Not comparable |
| MCP AtlasSource | 55.9% | — | Not comparable |
| Claw-EvalSource | 62.3% | — | Not comparable |
| DeepSearchQASource | 92.5% | — | Not comparable |
| WideResearchSource | 80.8% | — | Not comparable |
| AA Agentic IndexSource | 30.3% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | 8.5% | Kimi K2.6 leads |
| GDPval-AASource | 34.5% | — | Not comparable |
| GDPval-AASource | 1189 | — | Not comparable |
| APEX-Agents-AASource | 28.5% | — | Not comparable |
| Gert LabsSource | 56.82% | — | Not comparable |
| ResearchClawBenchSource | 18.0% | — | Not comparable |
| OSWorld 2.0Source | 4.6% | — | Not comparable |
| terminalBenchHardSource | 43.9% | — | Not comparable |
Coding10 benchmarks
| Benchmark | Kimi K2.6 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.2% | — | Not comparable |
| LiveCodeBench v6Source | 89.6% | — | Not comparable |
| SWE-bench ProSource | 58.6% | — | Not comparable |
| SWE MultilingualSource | 76.7% | — | Not comparable |
| SciCodeSource | 52.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 66.7% | — | Not comparable |
| Vibe Code BenchSource | 37.89% | — | Not comparable |
| cursorBench31Source | 47.6% | — | Not comparable |
| AA Coding IndexSource | 61.8% | — | Not comparable |
| AA-SciCodeSource | 53.5% | 3.0% | Kimi K2.6 leads |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | Kimi K2.6 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| GPQASource | 90.5% | — | Not comparable |
| GPQA-DSource | 90.5% | — | Not comparable |
| HLESource | 34.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 44.2% | 1.0% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 91.1% | 28.9% | Kimi K2.6 leads |
| AA-HLESource | 35.9% | 5.1% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | 6.4% | -83.9% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 32.8% | 5.2% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 39.3% | 94.0% | Kimi K2.6 leads |
Math5 benchmarks
Multimodal10 benchmarks
| Benchmark | Kimi K2.6 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| MMMU-ProSource | 79.4% | — | Not comparable |
| MMMU-Pro w/ PythonSource | 80.1% | — | Not comparable |
| CharXivSource | 80.4% | — | Not comparable |
| MathVisionSource | 87.4% | — | Not comparable |
| V*Source | 96.9% | — | Not comparable |
| AA-MMMU-ProSource | 79.4% | 26.5% | Kimi K2.6 leads |
| Design Arena WebsiteSource | 1306 | — | Not comparable |
| Liquid Extract JSON ValiditySource | — | 99.6% | Not comparable |
| Liquid Extract F1Source | — | 99.6% | Not comparable |
| Liquid Extract VLM JudgeSource | — | 90.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Kimi K2.6 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.0% | 33.1% | Kimi K2.6 leads |
Frequently Asked Questions (3)
Can I compare Kimi K2.6 and LFM2.5-VL-1.6B-Extract on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Kimi K2.6 and LFM2.5-VL-1.6B-Extract today?
Kimi K2.6: $0.95 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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