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Model comparison

LFM2.5-VL-450M vs MAI-Thinking-1

Data verified

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

N/A
No comparison
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0 category wins2 category wins

Evidence parity. LFM2.5-VL-450M and MAI-Thinking-1 share 2 comparable benchmark results. 2 of 8 categories are comparable. 5 results are unique to LFM2.5-VL-450M; 11 to MAI-Thinking-1.

Updated July 23, 2026
Shared results
2
LFM2.5-VL-450M only
5
MAI-Thinking-1 only
11
Comparable categories
2 / 8

Treat this as a split decision. LFM2.5-VL-450M makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; MAI-Thinking-1 is the better fit if knowledge is the priority or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 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-VL-450M 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 is the reasoning model in the pair, while LFM2.5-VL-450M 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. MAI-Thinking-1 gives you the larger context window at 256K, compared with 128K for LFM2.5-VL-450M.

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-VL-450M and MAI-Thinking-1
CategoryLFM2.5-VL-450MΔMAI-Thinking-1
KnowledgeLFM2.5-VL-450M20.5Margin→ 52.0MAI-Thinking-172.5
Inst. FollowingLFM2.5-VL-450M61.2Margin→ 23.8MAI-Thinking-185.0
AgenticLFM2.5-VL-450MNot measuredMarginNo overlapMAI-Thinking-146.0
CodingLFM2.5-VL-450MNot measuredMarginNo overlapMAI-Thinking-165.5
MathLFM2.5-VL-450MNot measuredMarginNo overlapMAI-Thinking-189.7

Decisive benchmark drivers

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

More
A · LFM2.5-VL-450MB · MAI-Thinking-1

  1. MMLU-Pro

    Knowledge
    Source ↗
    A 19.3%B 85%
    Winner: MAI-Thinking-1Δ 65.7
    MMLU-Pro: LFM2.5-VL-450M scored 19.3%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.

  2. GPQA

    Knowledge
    Source ↗
    A 25.7%B 84.2%
    Winner: MAI-Thinking-1Δ 58.5
    GPQA: LFM2.5-VL-450M scored 25.7%; MAI-Thinking-1 scored 84.2%. 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-VL-450MMAI-Thinking-1Comparison
Input / output priceUSD per 1M tokensLFM2.5-VL-450M$0 input / $0 outputMAI-Thinking-1Not availableA complete price comparison is not available.
Generation speedtokens per secondLFM2.5-VL-450MNot availableMAI-Thinking-1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLFM2.5-VL-450MNot availableMAI-Thinking-1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensLFM2.5-VL-450M128KMAI-Thinking-1256KMAI-Thinking-1 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLFM2.5-VL-450MMAI-Thinking-1Result
BFCL v4Source 21.1%—Not comparable
Terminal-Bench 2.0Source —46%Not comparable
Coding
BenchmarkLFM2.5-VL-450MMAI-Thinking-1Result
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-VL-450MMAI-Thinking-1Result
Graphwalks BFS 128KSource —90%Not comparable
KnowledgeMAI-Thinking-1 wins
BenchmarkLFM2.5-VL-450MMAI-Thinking-1Result
GPQASource 25.7%84.2%MAI-Thinking-1 leads
MMLU-ProSource 19.3%85%MAI-Thinking-1 leads
GPQA-DSource —84.2%Not comparable
SimpleQASource —31%Not comparable
Math
BenchmarkLFM2.5-VL-450MMAI-Thinking-1Result
AIME 2025Source —97%Not comparable
AIME26Source —94.5%Not comparable
HMMT Feb 2026Source —84.9%Not comparable
Multimodal
BenchmarkLFM2.5-VL-450MMAI-Thinking-1Result
MMMUSource 32.7%—Not comparable
RealWorldQASource 58.4%—Not comparable
CountBenchSource 73.3%—Not comparable
Inst. FollowingMAI-Thinking-1 wins
BenchmarkLFM2.5-VL-450MMAI-Thinking-1Result
IFEvalSource 61.2%—Not comparable
IFBenchSource —85%Not comparable
Frequently Asked Questions (3)

Which is better, LFM2.5-VL-450M or MAI-Thinking-1?

LFM2.5-VL-450M 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 knowledge tasks, LFM2.5-VL-450M or MAI-Thinking-1?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 20.5. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.

Which is better for instruction following, LFM2.5-VL-450M or MAI-Thinking-1?

MAI-Thinking-1 has the edge for instruction following in this comparison, averaging 85 versus 61.2. LFM2.5-VL-450M stays close enough that the answer can still flip depending on your workload.

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Last updated: July 23, 2026

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