Reasoning
Like-for-like- Pokee-Isaac 28B
- 60.7
- Qwen3.7 Max
- 90.4
- Weighted basis
- 1 vs 1 rows
- Reading
- Qwen3.7 Max leads
Model comparison
Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
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 based on different benchmark sets are marked directional and do not name a winner.
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.
Prompts that approach the documented context limit
Pokee-Isaac 28B
Pokee-Isaac 28B has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
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
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: rate-fallback
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
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
| Category | Pokee-Isaac 28B | Qwen3.7 Max | Weighted basis | Reading |
|---|---|---|---|---|
| Reasoning | 60.7 | 90.4 | Like-for-like1 vs 1 rows | Qwen3.7 Max leads |
| Agentic | Not measured | 69.7 | Not comparable0 vs 1 rows | Not comparable |
| Coding | Not measured | 77.9 | Not comparable0 vs 4 rows | Not comparable |
| Knowledge | Not measured | 64.2 | Not comparable0 vs 4 rows | Not comparable |
| Math | Not measured | 97.1 | Not comparable0 vs 1 rows | Not comparable |
| Multilingual | Not measured | 87.0 | Not comparable0 vs 1 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | 84.4 | Not comparable0 vs 2 rows | Not comparable |
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.
MRCRv2
Reasoning
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.
1K fresh input + 500 output tokens
Qwen3.7 Max has no comparable published API token rate.
50K fresh input + 3K output tokens
Qwen3.7 Max has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Pokee-Isaac 28B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.7 Max has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Pokee-Isaac 28B
Qwen3.7 Max
1M
Pokee-Isaac 28B
pokee-isaac
Pokee-Isaac 28B model pageQwen3.7 Max
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Pokee-Isaac 28B
Not published
Pokee-Isaac 28B model pageQwen3.7 Max
No comparable hosted API rate
Pokee-Isaac 28B
Not sourced
Qwen3.7 Max
Not sourced
Pokee-Isaac 28B
Not sourced
Qwen3.7 Max
Not sourced
Pokee-Isaac 28B
Not sourced
Qwen3.7 Max
Not sourced
Pokee-Isaac 28B
Reasoning
Qwen3.7 Max
Reasoning
Pokee-Isaac 28B
Proprietary
Qwen3.7 Max
Proprietary
Pokee-Isaac 28B
Proprietary
Qwen3.7 Max
Proprietary
Pokee-Isaac 28B
2026-08-03
Qwen3.7 Max
2026-05-16
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.1
Not directly comparable
BFCL v4
Qwen3.7 Max leads this result
τ³-bench results
Not directly comparable
MCP-Atlas claim coverage
Not directly comparable
PinchBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
QwenClawBench
Not directly comparable
Claw-Eval
Not directly comparable
MCP Atlas
Not directly comparable
VITA-Bench
Not directly comparable
HLE w/ tools
Not directly comparable
Gert Labs
Not directly comparable
ResearchClawBench
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
SWE-bench Verified
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
NL2Repo
Not directly comparable
SciCode
Not directly comparable
LiveCodeBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
GPQA
Not directly comparable
GPQA-D
Not directly comparable
HLE
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Redux
Not directly comparable
SuperGPQA
Not directly comparable
MMMLU
Not directly comparable
MMLU-ProX
Not directly comparable
NOVA-63
Not directly comparable
INCLUDE
Not directly comparable
MAXIFE
Not directly comparable
PolyMath
Not directly comparable
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.
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Pokee-Isaac 28B has the larger documented context window: 10M, compared with 1M.
Last updated August 4, 2026
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