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Model comparison

LFM2.5-8B-A1B vs MAI-Thinking-1

Data verified

Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

41.42/100
No comparison
N/A
0 category wins2 category wins

Public leaderboard positions: LFM2.5-8B-A1B #166 (Estimated); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. LFM2.5-8B-A1B and MAI-Thinking-1 share 3 comparable benchmark results. 2 of 8 categories are comparable. 14 results are unique to LFM2.5-8B-A1B; 10 to MAI-Thinking-1.

Updated July 23, 2026
Shared results
3
LFM2.5-8B-A1B only
14
MAI-Thinking-1 only
10
Comparable categories
2 / 8

Treat this as a split decision. LFM2.5-8B-A1B makes more sense if its workflow fits your team better; MAI-Thinking-1 is the better fit if mathematics is the priority or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 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

LFM2.5-8B-A1B and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

MAI-Thinking-1 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 scores and score margins for LFM2.5-8B-A1B and MAI-Thinking-1
CategoryLFM2.5-8B-A1BΔMAI-Thinking-1
MathLFM2.5-8B-A1B50.0Margin→ 39.7MAI-Thinking-189.7
Inst. FollowingLFM2.5-8B-A1B68.8Margin→ 16.2MAI-Thinking-185.0
AgenticLFM2.5-8B-A1BNot measuredMarginNo overlapMAI-Thinking-146.0
CodingLFM2.5-8B-A1BNot measuredMarginNo overlapMAI-Thinking-165.5
KnowledgeLFM2.5-8B-A1BNot measuredMarginNo overlapMAI-Thinking-172.5

Decisive benchmark drivers

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

More
A · LFM2.5-8B-A1BB · MAI-Thinking-1

  1. AIME26

    Math
    Source ↗
    A 50.0%B 94.5%
    Winner: MAI-Thinking-1Δ 44.5
    AIME26: LFM2.5-8B-A1B scored 50.0%; MAI-Thinking-1 scored 94.5%. MAI-Thinking-1 wins this benchmark.

  2. IFBench

    Inst. Following
    Source ↗
    A 56.5%B 85%
    Winner: MAI-Thinking-1Δ 28.5
    IFBench: LFM2.5-8B-A1B scored 56.5%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.

Operational comparison

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

MetricLFM2.5-8B-A1BMAI-Thinking-1Comparison
Input / output priceUSD per 1M tokensLFM2.5-8B-A1B$0 input / $0 outputMAI-Thinking-1Not availableA complete price comparison is not available.
Generation speedtokens per secondLFM2.5-8B-A1BNot availableMAI-Thinking-1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLFM2.5-8B-A1BNot availableMAI-Thinking-1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensLFM2.5-8B-A1B128KMAI-Thinking-1256KMAI-Thinking-1 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLFM2.5-8B-A1BMAI-Thinking-1Result
BFCL v4Source 49.7%—Not comparable
τ²-bench resultsSource 16.1%—Not comparable
Terminal-Bench 2.0Source —46%Not comparable
Coding
BenchmarkLFM2.5-8B-A1BMAI-Thinking-1Result
AA-SciCodeSource 7.8%—Not comparable
SWE-bench VerifiedSource —73.5%Not comparable
SWE-bench ProSource —52.8%Not comparable
Terminal-Bench 2.0Source —46.0%Not comparable
Reasoning
BenchmarkLFM2.5-8B-A1BMAI-Thinking-1Result
AA-LCRSource 0.0%—Not comparable
CritPtSource 0.0%—Not comparable
Graphwalks BFS 128KSource —90%Not comparable
Knowledge
BenchmarkLFM2.5-8B-A1BMAI-Thinking-1Result
AA-GPQA DiamondSource 51.3%—Not comparable
AA-HLESource 6.9%—Not comparable
AA-Omniscience IndexSource -33.3%—Not comparable
AA-Omniscience AccuracySource 9.4%—Not comparable
AA-Omniscience Hallucination RateSource 47.0%—Not comparable
Artificial Analysis Intelligence IndexSource 8.3%—Not comparable
GPQASource —84.2%Not comparable
GPQA-DSource —84.2%Not comparable
MMLU-ProSource —85%Not comparable
SimpleQASource —31%Not comparable
MathMAI-Thinking-1 wins
BenchmarkLFM2.5-8B-A1BMAI-Thinking-1Result
MATH-500Source 88.8%—Not comparable
AIME 2025Source 42.5%97%MAI-Thinking-1 leads
AIME26Source 50.0%94.5%MAI-Thinking-1 leads
HMMT Feb 2026Source —84.9%Not comparable
Inst. FollowingMAI-Thinking-1 wins
BenchmarkLFM2.5-8B-A1BMAI-Thinking-1Result
IFEvalSource 91.8%—Not comparable
IFBenchSource 56.5%85%MAI-Thinking-1 leads
AA-IFBenchSource 55.6%—Not comparable
Frequently Asked Questions (3)

Which is better, LFM2.5-8B-A1B or MAI-Thinking-1?

LFM2.5-8B-A1B and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for math, LFM2.5-8B-A1B or MAI-Thinking-1?

MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 50. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.

Which is better for instruction following, LFM2.5-8B-A1B or MAI-Thinking-1?

MAI-Thinking-1 has the edge for instruction following in this comparison, averaging 85 versus 68.8. Inside this category, IFBench is the benchmark that creates the most daylight between them.

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