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Model comparison

LFM2.5-8B-A1B vs Qwen3.6-27B

Data verified

Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

41.25/100
Margin
12.5pts
winning →
53.73/100
0 category wins1 category wins

Verified leaderboard positions: LFM2.5-8B-A1B unranked; Qwen3.6-27B #27

BenchAlign evidence: LFM2.5-8B-A1B estimated; Qwen3.6-27B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. LFM2.5-8B-A1B and Qwen3.6-27B share 13 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to LFM2.5-8B-A1B; 42 to Qwen3.6-27B.

Updated July 16, 2026
Shared results
13
LFM2.5-8B-A1B only
5
Qwen3.6-27B only
42
Comparable categories
1 / 8

Pick Qwen3.6-27B if you want the stronger benchmark profile. LFM2.5-8B-A1B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.

Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 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

Qwen3.6-27B is clearly ahead on the provisional aggregate, 66 to 37. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.6-27B's sharpest advantage is in mathematics, where it averages 89.2 against 50. The single biggest benchmark swing on the page is AIME26, 50.0% to 94.1%.

Qwen3.6-27B gives you the larger context window at 262K, 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 scores and score margins for LFM2.5-8B-A1B and Qwen3.6-27B
CategoryLFM2.5-8B-A1BΔQwen3.6-27B
MathLFM2.5-8B-A1B50.0Margin→ 39.2Qwen3.6-27B89.2
AgenticLFM2.5-8B-A1BNot measuredMarginNo overlapQwen3.6-27B59.3
CodingLFM2.5-8B-A1BNot measuredMarginNo overlapQwen3.6-27B77.5
KnowledgeLFM2.5-8B-A1BNot measuredMarginNo overlapQwen3.6-27B53.6
MultimodalLFM2.5-8B-A1BNot measuredMarginNo overlapQwen3.6-27B76.7
Inst. FollowingLFM2.5-8B-A1B68.8MarginNo overlapQwen3.6-27BNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · LFM2.5-8B-A1BB · Qwen3.6-27B

  1. AIME26

    Math
    Source ↗
    A 50.0%B 94.1%
    Winner: Qwen3.6-27BΔ 44.1
    AIME26: LFM2.5-8B-A1B scored 50.0%; Qwen3.6-27B scored 94.1%. Qwen3.6-27B wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricLFM2.5-8B-A1BQwen3.6-27BComparison
Input / output priceUSD per 1M tokensLFM2.5-8B-A1B$0 input / $0 outputQwen3.6-27B$0 input / $0 outputListed prices are equal.
Generation speedtokens per secondLFM2.5-8B-A1BNot availableQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLFM2.5-8B-A1BNot availableQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensLFM2.5-8B-A1B128KQwen3.6-27B262KQwen3.6-27B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
BFCL v4Source 49.7%—Not comparable
τ²-bench resultsSource 16.1%94.2%Qwen3.6-27B leads
Terminal-Bench 2.0Source —59.3%Not comparable
Claw-EvalSource —72.4%Not comparable
QwenClawBenchSource —53.4%Not comparable
QwenWebBenchSource —1487Not comparable
AndroidWorldSource —70.3%Not comparable
AA Agentic IndexSource —27.0%Not comparable
GDPval-AASource —32.0%Not comparable
GDPval-AASource —1140Not comparable
Gert LabsSource —54.84%Not comparable
Coding
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
Terminal-Bench HardSource 4.5%34.8%Qwen3.6-27B leads
AA-SciCodeSource 7.8%39.8%Qwen3.6-27B leads
SWE-bench VerifiedSource —77.2%Not comparable
SWE MultilingualSource —71.3%Not comparable
SWE-bench ProSource —53.5%Not comparable
Terminal-Bench 2.0Source —59.3%Not comparable
LiveCodeBenchSource —83.9%Not comparable
NL2RepoSource —36.2%Not comparable
AA Coding IndexSource —53.7%Not comparable
Reasoning
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
AA-LCRSource 0.0%68.7%Qwen3.6-27B leads
CritPtSource 0.0%1.1%Qwen3.6-27B leads
Knowledge
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
AA-GPQA DiamondSource 51.3%84.2%Qwen3.6-27B leads
AA-HLESource 6.9%21.6%Qwen3.6-27B leads
AA-Omniscience IndexSource -33.3%-19.8%Qwen3.6-27B leads
AA-Omniscience AccuracySource 9.4%19.2%Qwen3.6-27B leads
AA-Omniscience Hallucination RateSource 47.0%48.3%LFM2.5-8B-A1B leads
Artificial Analysis Intelligence IndexSource 8.3%37.0%Qwen3.6-27B leads
MMLU-ProSource —86.2%Not comparable
MMLU-ReduxSource —93.5%Not comparable
SuperGPQASource —66%Not comparable
C-EvalSource —91.4%Not comparable
GPQASource —87.8%Not comparable
HLESource —24%Not comparable
MathQwen3.6-27B wins
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
MATH-500Source 88.8%—Not comparable
AIME 2025Source 42.5%—Not comparable
AIME26Source 50.0%94.1%Qwen3.6-27B leads
HMMT Feb 2025Source —93.8%Not comparable
HMMT Nov 2025Source —90.7%Not comparable
HMMT Feb 2026Source —84.3%Not comparable
MMAnswerBenchSource —80.8%Not comparable
Multimodal
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
MMMUSource —82.9%Not comparable
MMMU-ProSource —75.8%Not comparable
RealWorldQASource —84.1%Not comparable
DynaMathSource —85.6%Not comparable
MStarSource —81.4%Not comparable
SimpleVQASource —56.1%Not comparable
CharXivSource —78.4%Not comparable
CC-OCRSource —81.2%Not comparable
CountBenchSource —97.8%Not comparable
RefCOCO (avg)Source —92.5%Not comparable
ERQASource —62.5%Not comparable
Video-MME (with subtitle)Source —87.7%Not comparable
VideoMMMUSource —84.4%Not comparable
MLVU (M-Avg)Source —86.6%Not comparable
V*Source —94.7%Not comparable
AA-MMMU-ProSource —74.6%Not comparable
Inst. Following
BenchmarkLFM2.5-8B-A1BQwen3.6-27BResult
IFEvalSource 91.8%—Not comparable
IFBenchSource 56.5%—Not comparable
AA-IFBenchSource 55.6%67.6%Qwen3.6-27B leads
Frequently Asked Questions (2)

Which is better, LFM2.5-8B-A1B or Qwen3.6-27B?

Qwen3.6-27B is ahead on BenchLM's provisional leaderboard, 66 to 37. The biggest single separator in this matchup is AIME26, where the scores are 50.0% and 94.1%.

Which is better for math, LFM2.5-8B-A1B or Qwen3.6-27B?

Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 50. Inside this category, AIME26 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.

LFM2.5-8B-A1B
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even—
Model the full break-even

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