Agentic
Directional only- LFM2.5-VL-450M
- 44.7
- Estimated · #98/151
- Qwen3.6-27B
- 33.9
- Supported · #133/151
- Basis
- BenchAlign lane · 1 vs 6 public rows
- Reading
- Directional only
LFM2.5-VL-450M vs Qwen3.6-27B
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
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.
5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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
Qwen3.6-27B
Qwen3.6-27B 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. Qwen3.6-27B 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.
2 LFM2.5-VL-450M only
5 Shared
33 Qwen3.6-27B only
- Shared results
- 5
- LFM2.5-VL-450M only
- 2
- Qwen3.6-27B only
- 33
- 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.
Knowledge
Directional only- LFM2.5-VL-450M
- 35.7
- Estimated · #160/181
- Qwen3.6-27B
- 49.0
- Estimated · #95/181
- Basis
- BenchAlign lane · 2 vs 6 public rows
- Reading
- Directional only
Coding
Not comparable- LFM2.5-VL-450M
- Not ranked
- Qwen3.6-27B
- 42.6
- Supported · #128/183
- Basis
- BenchAlign lane · 0 vs 6 public rows
- Reading
- Not comparable
Reasoning
Not comparable- LFM2.5-VL-450M
- Not ranked
- Qwen3.6-27B
- 73.7
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- LFM2.5-VL-450M
- Not ranked
- Qwen3.6-27B
- 72.8
- Unranked · 5 rankable rows
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- LFM2.5-VL-450M
- Not ranked
- Qwen3.6-27B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- LFM2.5-VL-450M
- Not ranked
- Qwen3.6-27B
- 51.5
- #35/48
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- LFM2.5-VL-450M
- Not ranked
- Qwen3.6-27B
- 82.2
- #50/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | LFM2.5-VL-450M | Qwen3.6-27B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 44.7Estimated · #98/151 | 33.9Supported · #133/151 | Directional onlyBenchAlign lane · 1 vs 6 public rows | Directional only |
| Knowledge | 35.7Estimated · #160/181 | 49.0Estimated · #95/181 | Directional onlyBenchAlign lane · 2 vs 6 public rows | Directional only |
| Coding | Not ranked | 42.6Supported · #128/183 | Not comparableBenchAlign lane · 0 vs 6 public rows | Not comparable |
| Reasoning | Not ranked | 73.7Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 72.8Unranked · 5 rankable rows | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 51.5#35/48 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Instruction following | Not ranked | 82.2#50/120 | Not comparableProvisional lane · 0 vs 0 weighted rows | 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.
MMLU-Pro
Knowledge
GPQA
Knowledge
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
- Qwen3.6-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
LFM2.5-VL-450M has no comparable published API token rate. Qwen3.6-27B 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
- Qwen3.6-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
LFM2.5-VL-450M has no comparable published API token rate. Qwen3.6-27B 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
- Qwen3.6-27B
- Self-hosted; infrastructure cost varies
- 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. Qwen3.6-27B 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.
SpecificationLFM2.5-VL-450MQwen3.6-27B
Context window
Maximum documented context; output-token limits may be lower.
LFM2.5-VL-450M
128K
Qwen3.6-27B
262K
API model ID
LFM2.5-VL-450M
Not sourced
Qwen3.6-27B
Not sourced
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
Qwen3.6-27B
No comparable hosted API rate
Documented inputs
LFM2.5-VL-450M
Not sourced
Qwen3.6-27B
Not sourced
Documented outputs
LFM2.5-VL-450M
Not sourced
Qwen3.6-27B
Not sourced
Provider availability
LFM2.5-VL-450M
Not sourced
Qwen3.6-27B
Not sourced
Reasoning profile
LFM2.5-VL-450M
Non-Reasoning
Qwen3.6-27B
Reasoning
Weight access
LFM2.5-VL-450M
Open Weight
Qwen3.6-27B
Open Weight
License
LFM2.5-VL-450M
Open Weight
Qwen3.6-27B
Open Weight
Release date
LFM2.5-VL-450M
2026-04-08
Qwen3.6-27B
2026-04-21
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
- Qwen3.6-27B has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
LFM2.5-VL-450M
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—
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence40 rows
Agentic
BFCL v4
LFM2.5-VL-450M21.1%SourceQwen3.6-27B—Not directly comparable
Terminal-Bench 2.0
LFM2.5-VL-450M—Qwen3.6-27B59.3%SourceNot directly comparable
Claw-Eval
LFM2.5-VL-450M—Qwen3.6-27B72.4%SourceNot directly comparable
QwenClawBench
LFM2.5-VL-450M—Qwen3.6-27B53.4%SourceNot directly comparable
QwenWebBench
LFM2.5-VL-450M—Qwen3.6-27B1487SourceNot directly comparable
AndroidWorld
LFM2.5-VL-450M—Qwen3.6-27B70.3%SourceNot directly comparable
Gert Labs
LFM2.5-VL-450M—Qwen3.6-27B54.84%SourceNot directly comparable
Coding
SWE-bench Verified
LFM2.5-VL-450M—Qwen3.6-27B77.2%SourceNot directly comparable
SWE Multilingual
LFM2.5-VL-450M—Qwen3.6-27B71.3%SourceNot directly comparable
SWE-bench Pro
LFM2.5-VL-450M—Qwen3.6-27B53.5%SourceNot directly comparable
Terminal-Bench 2.0
LFM2.5-VL-450M—Qwen3.6-27B59.3%SourceNot directly comparable
LiveCodeBench
LFM2.5-VL-450M—Qwen3.6-27B83.9%SourceNot directly comparable
NL2Repo
LFM2.5-VL-450M—Qwen3.6-27B36.2%SourceNot directly comparable
Knowledge
GPQA
LFM2.5-VL-450M25.7%SourceQwen3.6-27B87.8%SourceQwen3.6-27B leads this result
MMLU-Pro
LFM2.5-VL-450M19.3%SourceQwen3.6-27B86.2%SourceQwen3.6-27B leads this result
MMLU-Redux
LFM2.5-VL-450M—Qwen3.6-27B93.5%SourceNot directly comparable
SuperGPQA
LFM2.5-VL-450M—Qwen3.6-27B66%SourceNot directly comparable
C-Eval
LFM2.5-VL-450M—Qwen3.6-27B91.4%SourceNot directly comparable
HLE
LFM2.5-VL-450M—Qwen3.6-27B24%SourceNot directly comparable
Math
HMMT Feb 2025
LFM2.5-VL-450M—Qwen3.6-27B93.8%SourceNot directly comparable
HMMT Nov 2025
LFM2.5-VL-450M—Qwen3.6-27B90.7%SourceNot directly comparable
HMMT Feb 2026
LFM2.5-VL-450M—Qwen3.6-27B84.3%SourceNot directly comparable
MMAnswerBench
LFM2.5-VL-450M—Qwen3.6-27B80.8%SourceNot directly comparable
AIME26
LFM2.5-VL-450M—Qwen3.6-27B94.1%SourceNot directly comparable
Multimodal
MMMU
LFM2.5-VL-450M32.7%SourceQwen3.6-27B82.9%SourceQwen3.6-27B leads this result
RealWorldQA
LFM2.5-VL-450M58.4%SourceQwen3.6-27B84.1%SourceQwen3.6-27B leads this result
CountBench
LFM2.5-VL-450M73.3%SourceQwen3.6-27B97.8%SourceQwen3.6-27B leads this result
MMMU-Pro
LFM2.5-VL-450M—Qwen3.6-27B75.8%SourceNot directly comparable
DynaMath
LFM2.5-VL-450M—Qwen3.6-27B85.6%SourceNot directly comparable
MStar
LFM2.5-VL-450M—Qwen3.6-27B81.4%SourceNot directly comparable
SimpleVQA
LFM2.5-VL-450M—Qwen3.6-27B56.1%SourceNot directly comparable
CharXiv
LFM2.5-VL-450M—Qwen3.6-27B78.4%SourceNot directly comparable
CC-OCR
LFM2.5-VL-450M—Qwen3.6-27B81.2%SourceNot directly comparable
RefCOCO (avg)
LFM2.5-VL-450M—Qwen3.6-27B92.5%SourceNot directly comparable
ERQA
LFM2.5-VL-450M—Qwen3.6-27B62.5%SourceNot directly comparable
Video-MME (with subtitle)
LFM2.5-VL-450M—Qwen3.6-27B87.7%SourceNot directly comparable
VideoMMMU
LFM2.5-VL-450M—Qwen3.6-27B84.4%SourceNot directly comparable
MLVU (M-Avg)
LFM2.5-VL-450M—Qwen3.6-27B86.6%SourceNot directly comparable
V*
LFM2.5-VL-450M—Qwen3.6-27B94.7%SourceNot directly comparable
Instruction following
IFEval
LFM2.5-VL-450M61.2%SourceQwen3.6-27B—Not directly comparable
Frequently asked questions
Which is better, LFM2.5-VL-450M or Qwen3.6-27B?
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 Qwen3.6-27B?
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 Qwen3.6-27B?
LFM2.5-VL-450M scores higher for agentic tasks on the public lane, 44.7 to 33.9. 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 Qwen3.6-27B?
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 Qwen3.6-27B?
Qwen3.6-27B has the larger documented context window: 262K, compared with 128K.
Related comparisons
Last updated September 4, 2026
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