Agentic
Not comparable- A.X K2
- Not ranked
- Qwen3.7 Max
- 41.2
- Supported · #110/152
- Basis
- BenchAlign lane · 1 vs 10 public rows
- Reading
- Not comparable
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Follow model changesUpdated 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.
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
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
Qwen3.7 Max
Qwen3.7 Max has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
A.X K2 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
A.X K2 is not ranked on the public lane for agentic, so no winner is named for agentic.
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: listed-rates
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 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.
| Category | A.X K2 | 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 · 3 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 · 2 vs 9 public rows | Not comparable |
| Math | Not ranked | 82.1Unranked · 3 rankable rows | Not comparableProvisional lane · 1 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 · 1 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.
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.
HLE
Knowledge
SciCode
Coding
IFBench
Instruction following
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
A.X K2 has no comparable published API token rate. Qwen3.7 Max has no comparable published API token rate.
50K fresh input + 3K output tokens
A.X K2 has no comparable published API token rate. Qwen3.7 Max has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
A.X K2 has no comparable published API token 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.
A.X K2
Qwen3.7 Max
1M
A.X K2
skt/A.X-K2
SK Telecom A.X K2 model cardQwen3.7 Max
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
A.X K2
No comparable hosted API rate
SK Telecom A.X K2 model cardQwen3.7 Max
No comparable hosted API rate
A.X K2
Not sourced
Qwen3.7 Max
Not sourced
A.X K2
Not sourced
Qwen3.7 Max
Not sourced
A.X K2
Not sourced
Qwen3.7 Max
Not sourced
A.X K2
Reasoning
Qwen3.7 Max
Reasoning
A.X K2
Open Weight
Qwen3.7 Max
Proprietary
A.X K2
Open Weight
Qwen3.7 Max
Proprietary
A.X K2
2026-07-29
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
Terminal-Bench 2.0
Not directly comparable
QwenClawBench
Not directly comparable
Claw-Eval
Not directly comparable
BFCL v4
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 (Vals)
Not directly comparable
LiveCodeBench v6
Not directly comparable
SciCode
Qwen3.7 Max leads this result
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
LiveCodeBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
OpenHarmony Bench
Not directly comparable
LiveCodeBench (Vals)
Not directly comparable
SWE-bench (Vals)
Not directly comparable
HLE
Qwen3.7 Max leads this result
GPQA-D
Qwen3.7 Max leads this result
GPQA
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Redux
Not directly comparable
SuperGPQA
Not directly comparable
MMMLU
Not directly comparable
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
AIME26
Not directly comparable
Apex
A.X K2 leads this result
Apex Shortlist
Not directly comparable
HMMT Feb 2026
Not directly comparable
IMOAnswerBench
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.
A.X K2 is not ranked on the public lane for coding, so no winner is named for coding.
A.X K2 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Qwen3.7 Max has the larger documented context window: 1M, compared with 262K.
Last updated September 10, 2026
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