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BenchLM

LFM2.5-VL-450M vs Qwen3.8 Max

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

LiquidAI logo
Model A
LFM2.5-VL-450M

LiquidAI

—

Evidence status unavailable

90% interval unavailable

Alibaba logo
Model B
Qwen3.8 Max

Alibaba

71.76/100

Supported · Public rank #11

90% interval 68.1–75.4

Updated September 15, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Qwen3.8 Max

    Qwen3.8 Max has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    LFM2.5-VL-450M is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    LFM2.5-VL-450M is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. LFM2.5-VL-450M does not fit this workload in one request. LFM2.5-VL-450M has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
2
LFM2.5-VL-450M only
5
Qwen3.8 Max only
58
Like-for-like categories
0 / 8

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Directional only
LFM2.5-VL-450M
42.5
Estimated · #105/153
Qwen3.8 Max
67.3
Supported · #9/153
Basis
BenchAlign lane · 1 vs 15 public rows
Reading
Directional only

Knowledge

Directional only
LFM2.5-VL-450M
34.0
Estimated · #165/183
Qwen3.8 Max
68.8
Supported · #17/183
Basis
BenchAlign lane · 2 vs 6 public rows
Reading
Directional only

Coding

Not comparable
LFM2.5-VL-450M
Not ranked
Qwen3.8 Max
60.8
Supported · #20/152
Basis
BenchAlign lane · 0 vs 12 public rows
Reading
Not comparable

Reasoning

Not comparable
LFM2.5-VL-450M
Not ranked
Qwen3.8 Max
86.5
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Math

Not comparable
LFM2.5-VL-450M
Not ranked
Qwen3.8 Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
LFM2.5-VL-450M
Not ranked
Qwen3.8 Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
LFM2.5-VL-450M
Not ranked
Qwen3.8 Max
87.4
#5/48
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Instruction following

Not comparable
LFM2.5-VL-450M
Not ranked
Qwen3.8 Max
90.7
#18/123
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

LFM2.5-VL-450M
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

LFM2.5-VL-450M has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

LFM2.5-VL-450M
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

LFM2.5-VL-450M has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

LFM2.5-VL-450M
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable
Qwen3.8 Max
API rate not published
Fits in one request
Cached-input rate unavailable

LFM2.5-VL-450M does not fit this workload in one request. LFM2.5-VL-450M has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

LFM2.5-VL-450M

No comparable hosted API rate

Qwen3.8 Max

No comparable hosted API rate

Alibaba Cloud Model Studio pricing

Documented inputs

LFM2.5-VL-450M

Not sourced

Qwen3.8 Max

Not sourced

Documented outputs

LFM2.5-VL-450M

Not sourced

Qwen3.8 Max

Not sourced

Provider availability

LFM2.5-VL-450M

Not sourced

Qwen3.8 Max

Not sourced

Reasoning profile

LFM2.5-VL-450M

Non-Reasoning

Qwen3.8 Max

Reasoning

Weight access

LFM2.5-VL-450M

Open Weight

Qwen3.8 Max

Open Weight

License

LFM2.5-VL-450M

Open Weight

Qwen3.8 Max

Open Weight

Release date

LFM2.5-VL-450M

2026-04-08

Qwen3.8 Max

2026-08-03

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Qwen3.8 Max has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence65 rows

Agentic

  • BFCL v4

    LFM2.5-VL-450M21.1%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • Terminal-Bench 2.1

    LFM2.5-VL-450M—
    Qwen3.8 Max86.6%
    Source

    Not directly comparable

  • CoWorkBench

    LFM2.5-VL-450M—
    Qwen3.8 Max74.8%
    Source

    Not directly comparable

  • JobBench

    LFM2.5-VL-450M—
    Qwen3.8 Max53.4%
    Source

    Not directly comparable

  • skillsBench

    LFM2.5-VL-450M—
    Qwen3.8 Max70.2%
    Source

    Not directly comparable

  • Agents' Last Exam

    LFM2.5-VL-450M—
    Qwen3.8 Max52.4%
    Source

    Not directly comparable

  • AutomationBench

    LFM2.5-VL-450M—
    Qwen3.8 Max27.3%
    Source

    Not directly comparable

  • Toolathlon-Verified

    LFM2.5-VL-450M—
    Qwen3.8 Max72.5%
    Source

    Not directly comparable

  • WideResearch

    LFM2.5-VL-450M—
    Qwen3.8 Max81.9%
    Source

    Not directly comparable

  • HLE w/ tools

    LFM2.5-VL-450M—
    Qwen3.8 Max56.2%
    Source

    Not directly comparable

  • OSWorld-Verified

    LFM2.5-VL-450M—
    Qwen3.8 Max86.1%
    Source

    Not directly comparable

  • OSWorld 2.0

    LFM2.5-VL-450M—
    Qwen3.8 Max19.4%
    Source

    Not directly comparable

  • WebArena-Verified

    LFM2.5-VL-450M—
    Qwen3.8 Max66.8%
    Source

    Not directly comparable

  • AndroidWorld

    LFM2.5-VL-450M—
    Qwen3.8 Max85.3%
    Source

    Not directly comparable

  • MobileWorld

    LFM2.5-VL-450M—
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    LFM2.5-VL-450M—
    Qwen3.8 Max67.4%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    LFM2.5-VL-450M—
    Qwen3.8 Max86.6%
    Source

    Not directly comparable

  • SWE-bench Pro

    LFM2.5-VL-450M—
    Qwen3.8 Max67.7%
    Source

    Not directly comparable

  • DeepSWE

    LFM2.5-VL-450M—
    Qwen3.8 Max56.6%
    Source

    Not directly comparable

  • NL2Repo

    LFM2.5-VL-450M—
    Qwen3.8 Max55.9%
    Source

    Not directly comparable

  • FrontierSWE

    LFM2.5-VL-450M—
    Qwen3.8 Max73.5%
    Source

    Not directly comparable

  • MLS-Bench Lite

    LFM2.5-VL-450M—
    Qwen3.8 Max41.0%
    Source

    Not directly comparable

  • PaperBench

    LFM2.5-VL-450M—
    Qwen3.8 Max93.0%
    Source

    Not directly comparable

  • VulcanBench v3

    LFM2.5-VL-450M—
    Qwen3.8 Max81.2%
    Source

    Not directly comparable

  • OpenHarmony Bench

    LFM2.5-VL-450M—
    Qwen3.8 Max60.8%
    Source

    Not directly comparable

  • FrontierSWE v2

    LFM2.5-VL-450M—
    Qwen3.8 Max15.8%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    LFM2.5-VL-450M—
    Qwen3.8 Max87.9%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    LFM2.5-VL-450M—
    Qwen3.8 Max85.6%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    LFM2.5-VL-450M—
    Qwen3.8 Max92.9%
    Source

    Not directly comparable

  • LongBench v2

    LFM2.5-VL-450M—
    Qwen3.8 Max66.3%
    Source

    Not directly comparable

Knowledge

  • GPQA

    LFM2.5-VL-450M25.7%
    Source
    Qwen3.8 Max92.6%
    Source

    Qwen3.8 Max leads this result

  • MMLU-Pro

    LFM2.5-VL-450M19.3%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • GPQA-D

    LFM2.5-VL-450M—
    Qwen3.8 Max92.6%
    Source

    Not directly comparable

  • HLE

    LFM2.5-VL-450M—
    Qwen3.8 Max43.6%
    Source

    Not directly comparable

  • HLE w/o tools

    LFM2.5-VL-450M—
    Qwen3.8 Max43.6%
    Source

    Not directly comparable

  • GPQA Diamond (Vals)

    LFM2.5-VL-450M—
    Qwen3.8 Max93.7%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    LFM2.5-VL-450M—
    Qwen3.8 Max88.6%
    Source

    Not directly comparable

Multimodal

  • MMMU

    LFM2.5-VL-450M32.7%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • RealWorldQA

    LFM2.5-VL-450M58.4%
    Source
    Qwen3.8 Max88.0%
    Source

    Qwen3.8 Max leads this result

  • CountBench

    LFM2.5-VL-450M73.3%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • MMMU-Pro

    LFM2.5-VL-450M—
    Qwen3.8 Max82.3%
    Source

    Not directly comparable

  • MathVision

    LFM2.5-VL-450M—
    Qwen3.8 Max95.2%
    Source

    Not directly comparable

  • MathVision w/ Python

    LFM2.5-VL-450M—
    Qwen3.8 Max97.7%
    Source

    Not directly comparable

  • BabyVision

    LFM2.5-VL-450M—
    Qwen3.8 Max82.0%
    Source

    Not directly comparable

  • BabyVision w/ Python

    LFM2.5-VL-450M—
    Qwen3.8 Max91.3%
    Source

    Not directly comparable

  • ZeroBench

    LFM2.5-VL-450M—
    Qwen3.8 Max24.0%
    Source

    Not directly comparable

  • ZeroBench w/ Python

    LFM2.5-VL-450M—
    Qwen3.8 Max49.0%
    Source

    Not directly comparable

  • MedXpertQA (MM)

    LFM2.5-VL-450M—
    Qwen3.8 Max80.4%
    Source

    Not directly comparable

  • ScreenSpot Pro

    LFM2.5-VL-450M—
    Qwen3.8 Max84.5%
    Source

    Not directly comparable

  • Vision2Web

    LFM2.5-VL-450M—
    Qwen3.8 Max69.0%
    Source

    Not directly comparable

  • CharXiv w/o tools

    LFM2.5-VL-450M—
    Qwen3.8 Max88.4%
    Source

    Not directly comparable

  • CharXiv

    LFM2.5-VL-450M—
    Qwen3.8 Max93.5%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    LFM2.5-VL-450M—
    Qwen3.8 Max92.1%
    Source

    Not directly comparable

  • OCRBench V2

    LFM2.5-VL-450M—
    Qwen3.8 Max74.2%
    Source

    Not directly comparable

  • CC-OCR

    LFM2.5-VL-450M—
    Qwen3.8 Max79.6%
    Source

    Not directly comparable

  • ERQA

    LFM2.5-VL-450M—
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

  • SimpleVQA

    LFM2.5-VL-450M—
    Qwen3.8 Max75.0%
    Source

    Not directly comparable

  • PerceptionBench

    LFM2.5-VL-450M—
    Qwen3.8 Max63.5%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    LFM2.5-VL-450M—
    Qwen3.8 Max90.4%
    Source

    Not directly comparable

  • VideoMMMU

    LFM2.5-VL-450M—
    Qwen3.8 Max88.7%
    Source

    Not directly comparable

  • MMVU

    LFM2.5-VL-450M—
    Qwen3.8 Max82.4%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    LFM2.5-VL-450M—
    Qwen3.8 Max90.8%
    Source

    Not directly comparable

  • LVBench

    LFM2.5-VL-450M—
    Qwen3.8 Max81.8%
    Source

    Not directly comparable

Instruction following

  • IFEval

    LFM2.5-VL-450M61.2%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • IFBench

    LFM2.5-VL-450M—
    Qwen3.8 Max82.8%
    Source

    Not directly comparable

Questions

Which is better, LFM2.5-VL-450M or Qwen3.8 Max?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, LFM2.5-VL-450M or Qwen3.8 Max?

LFM2.5-VL-450M is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, LFM2.5-VL-450M or Qwen3.8 Max?

Qwen3.8 Max scores higher for agentic tasks on the public lane, 67.3 to 42.5. LFM2.5-VL-450M is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, LFM2.5-VL-450M or Qwen3.8 Max?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, LFM2.5-VL-450M or Qwen3.8 Max?

Qwen3.8 Max has the larger documented context window: 1M, compared with 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 15, 2026

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