Agentic
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 41.2
- Supported · #110/152
- Basis
- BenchAlign lane · 1 vs 10 public rows
- Reading
- Not comparable
BTL-3 vs Qwen3.7 Max
Updated September 10, 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.
1 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
Qwen3.7 Max
Qwen3.7 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
BTL-3 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
BTL-3 is not ranked on the public lane for agentic, so no winner is named for agentic.
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
A complete comparable API-rate estimate is not available for both models.
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 BTL-3 only
1 Shared
40 Qwen3.7 Max only
- Shared results
- 1
- BTL-3 only
- 2
- Qwen3.7 Max only
- 40
- Like-for-like categories
- 0 / 8
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.
Coding
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 49.3
- Supported · #64/151
- Basis
- BenchAlign lane · 2 vs 10 public rows
- Reading
- Not comparable
Reasoning
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 75.1
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 61.7
- Supported · #28/183
- Basis
- BenchAlign lane · 0 vs 9 public rows
- Reading
- Not comparable
Math
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 82.1
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 100.0
- #1/12
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- BTL-3
- Not ranked
- Qwen3.7 Max
- 91.1
- #16/123
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | BTL-3 | Qwen3.7 Max | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 41.2Supported · #110/152 | Not comparableBenchAlign lane · 1 vs 10 public rows | Not comparable |
| Coding | Not ranked | 49.3Supported · #64/151 | Not comparableBenchAlign lane · 2 vs 10 public rows | Not comparable |
| Reasoning | Not ranked | 75.1Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Knowledge | Not ranked | 61.7Supported · #28/183 | Not comparableBenchAlign lane · 0 vs 9 public rows | Not comparable |
| Math | Not ranked | 82.1Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | 100.0#1/12 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 91.1#16/123 | Not comparableProvisional lane · 0 vs 1 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
- BTL-3
- Self-hosted; infrastructure cost varies
- Fits in one request
- Qwen3.7 Max
- API rate not published
- Fits in one request
BTL-3 has no comparable published API token rate. Qwen3.7 Max has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- BTL-3
- Self-hosted; infrastructure cost varies
- Fits in one request
- Qwen3.7 Max
- API rate not published
- Fits in one request
BTL-3 has no comparable published API token rate. Qwen3.7 Max has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- BTL-3
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
- Qwen3.7 Max
- API rate not published
- Fits in one request
- Cached-input rate unavailable
BTL-3 has no comparable published API token rate. Qwen3.7 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.
SpecificationBTL-3Qwen3.7 Max
Context window
Maximum documented context; output-token limits may be lower.
BTL-3
Qwen3.7 Max
1M
API model ID
BTL-3
badtheorylabs/BTL-3
Bad Theory Labs BTL-3 model cardQwen3.7 Max
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
BTL-3
No comparable hosted API rate
Bad Theory Labs BTL-3 model cardQwen3.7 Max
No comparable hosted API rate
Documented inputs
BTL-3
Not sourced
Qwen3.7 Max
Not sourced
Documented outputs
BTL-3
Not sourced
Qwen3.7 Max
Not sourced
Provider availability
BTL-3
Not sourced
Qwen3.7 Max
Not sourced
Reasoning profile
BTL-3
Reasoning
Qwen3.7 Max
Reasoning
Weight access
BTL-3
Open Weight
Qwen3.7 Max
Proprietary
License
BTL-3
Open Weight
Qwen3.7 Max
Proprietary
Release date
BTL-3
2026-07-20
Qwen3.7 Max
2026-05-16
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
- Qwen3.7 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 evidence43 rows
Agentic
BFCL v4
BTL-388.5%SourceQwen3.7 Max75.0%SourceBTL-3 leads this result
Terminal-Bench 2.0
BTL-3—Qwen3.7 Max69.7%SourceNot directly comparable
QwenClawBench
BTL-3—Qwen3.7 Max64.3%SourceNot directly comparable
Claw-Eval
BTL-3—Qwen3.7 Max65.2%SourceNot directly comparable
MCP Atlas
BTL-3—Qwen3.7 Max76.4%SourceNot directly comparable
VITA-Bench
BTL-3—Qwen3.7 Max47.9%SourceNot directly comparable
HLE w/ tools
BTL-3—Qwen3.7 Max53.5%SourceNot directly comparable
Gert Labs
BTL-3—Qwen3.7 Max64.27%SourceNot directly comparable
ResearchClawBench
BTL-3—Qwen3.7 Max18.7%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
BTL-3—Qwen3.7 Max61.0%SourceNot directly comparable
Coding
HumanEval
BTL-395.1%SourceQwen3.7 Max—Not directly comparable
LiveCodeBench v6
BTL-388.1%SourceQwen3.7 Max—Not directly comparable
SWE-bench Verified
BTL-3—Qwen3.7 Max80.4%SourceNot directly comparable
SWE-bench Pro
BTL-3—Qwen3.7 Max60.6%SourceNot directly comparable
SWE Multilingual
BTL-3—Qwen3.7 Max78.3%SourceNot directly comparable
NL2Repo
BTL-3—Qwen3.7 Max47.2%SourceNot directly comparable
SciCode
BTL-3—Qwen3.7 Max53.5%SourceNot directly comparable
LiveCodeBench
BTL-3—Qwen3.7 Max91.6%SourceNot directly comparable
Terminal-Bench 2.0
BTL-3—Qwen3.7 Max69.7%SourceNot directly comparable
OpenHarmony Bench
BTL-3—Qwen3.7 Max53.4%SourceNot directly comparable
LiveCodeBench (Vals)
BTL-3—Qwen3.7 Max87.1%SourceNot directly comparable
SWE-bench (Vals)
BTL-3—Qwen3.7 Max68.8%SourceNot directly comparable
Reasoning
Knowledge
GPQA
BTL-3—Qwen3.7 Max92.4%SourceNot directly comparable
GPQA-D
BTL-3—Qwen3.7 Max92.4%SourceNot directly comparable
HLE
BTL-3—Qwen3.7 Max41.4%SourceNot directly comparable
MMLU-Pro
BTL-3—Qwen3.7 Max89.6%SourceNot directly comparable
MMLU-Redux
BTL-3—Qwen3.7 Max95%SourceNot directly comparable
SuperGPQA
BTL-3—Qwen3.7 Max73.6%SourceNot directly comparable
MMMLU
BTL-3—Qwen3.7 Max90.3%SourceNot directly comparable
GPQA Diamond (Vals)
BTL-3—Qwen3.7 Max90.2%SourceNot directly comparable
MMLU-Pro (Vals)
BTL-3—Qwen3.7 Max89.3%SourceNot directly comparable
Math
Multilingual
Instruction following
Frequently asked questions
Which is better, BTL-3 or Qwen3.7 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, BTL-3 or Qwen3.7 Max?
BTL-3 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, BTL-3 or Qwen3.7 Max?
BTL-3 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, BTL-3 or Qwen3.7 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, BTL-3 or Qwen3.7 Max?
Qwen3.7 Max has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 10, 2026
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