Agentic
Like-for-like- Nemotron 3 Ultra
- 22.2
- Supported · #150/151
- Qwen3.7 Plus
- 37.7
- Supported · #126/151
- Basis
- BenchAlign lane · 6 vs 11 public rows
- Reading
- Qwen3.7 Plus leads
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Qwen3.7 Plus has the higher public score, 62.29 versus 40.67, and the 90% score intervals do not overlap.
13 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.
Tool use, computer use, and multi-step task completion
Qwen3.7 Plus
Qwen3.7 Plus leads on the public agentic lane, 37.7 to 22.2, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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.
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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 | Nemotron 3 Ultra | Qwen3.7 Plus | Basis | Reading |
|---|---|---|---|---|
| Agentic | 22.2Supported · #150/151 | 37.7Supported · #126/151 | Like-for-likeBenchAlign lane · 6 vs 11 public rows | Qwen3.7 Plus leads |
| Multilingual | 47.4#7/12 | 78.9#3/12 | Like-for-likeProvisional lane · 1 vs 1 weighted rows | Qwen3.7 Plus leads |
| Instruction following | 88.7#28/120 | 91.1#17/120 | Like-for-likeProvisional lane · 1 vs 1 weighted rows | Qwen3.7 Plus leads |
| Coding | 26.9Supported · #174/183 | 53.1Estimated · #51/183 | Directional onlyBenchAlign lane · 7 vs 7 public rows | Directional only |
| Knowledge | 45.6Estimated · #114/181 | 56.8Estimated · #50/181 | Directional onlyBenchAlign lane · 7 vs 7 public rows | Directional only |
| Reasoning | 48.7Unranked · 1 rankable row | 73.7Unranked · 3 rankable rows | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Math | Not ranked | 78.3Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | 72.5#18/48 | Not comparableProvisional lane · 0 vs 2 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.
Terminal-Bench 2.0
Agentic
SWE Multilingual
Coding
HLE
Knowledge
SciCode
Coding
SWE-bench Verified
Coding
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
Nemotron 3 Ultra has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.
50K fresh input + 3K output tokens
Nemotron 3 Ultra has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Nemotron 3 Ultra has no comparable published API token rate. Qwen3.7 Plus 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.
Nemotron 3 Ultra
1M
Qwen3.7 Plus
1M
Nemotron 3 Ultra
Not sourced
Qwen3.7 Plus
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Nemotron 3 Ultra
No comparable hosted API rate
Qwen3.7 Plus
No comparable hosted API rate
Nemotron 3 Ultra
Not sourced
Qwen3.7 Plus
Not sourced
Nemotron 3 Ultra
Not sourced
Qwen3.7 Plus
Not sourced
Nemotron 3 Ultra
Not sourced
Qwen3.7 Plus
Not sourced
Nemotron 3 Ultra
Reasoning
Qwen3.7 Plus
Reasoning
Nemotron 3 Ultra
Open Weight
Qwen3.7 Plus
Proprietary
Nemotron 3 Ultra
Open Weight
Qwen3.7 Plus
Proprietary
Nemotron 3 Ultra
2026-06-04
Qwen3.7 Plus
2026-06-03
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 2.0
Qwen3.7 Plus leads this result
PinchBench
Not directly comparable
BrowseComp
Not directly comparable
τ³-bench results
Not directly comparable
HLE w/ tools
Not directly comparable
Terminal-Bench 2.1 (Vals)
Qwen3.7 Plus leads this result
QwenClawBench
Not directly comparable
Claw-Eval
Not directly comparable
BFCL v4
Not directly comparable
MCP Atlas
Not directly comparable
VITA-Bench
Not directly comparable
DeepPlanning
Not directly comparable
OSWorld-Verified
Not directly comparable
AndroidWorld
Not directly comparable
OSWorld 2.0
Not directly comparable
SWE-bench Verified
Qwen3.7 Plus leads this result
SWE Multilingual
Qwen3.7 Plus leads this result
LiveCodeBench v6
Not directly comparable
SciCode
Qwen3.7 Plus leads this result
Terminal-Bench 2.0
Qwen3.7 Plus leads this result
LiveCodeBench (Vals)
Not directly comparable
SWE-bench (Vals)
Not directly comparable
SWE-bench Pro
Not directly comparable
NL2Repo
Not directly comparable
LiveCodeBench
Not directly comparable
GPQA
Qwen3.7 Plus leads this result
GPQA-D
Qwen3.7 Plus leads this result
HLE
Qwen3.7 Plus leads this result
HLE w/o tools
Not directly comparable
MMLU-Pro
Qwen3.7 Plus leads this result
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
MMLU-Redux
Not directly comparable
SuperGPQA
Not directly comparable
MMMLU
Not directly comparable
MMLU-ProX
Qwen3.7 Plus leads this result
NOVA-63
Not directly comparable
INCLUDE
Not directly comparable
MAXIFE
Not directly comparable
PolyMath
Not directly comparable
MMMU-Pro
Not directly comparable
MathVision
Not directly comparable
CharXiv
Not directly comparable
ERQA
Not directly comparable
MedXpertQA (MM)
Not directly comparable
ScreenSpot Pro
Not directly comparable
SimpleVQA
Not directly comparable
MMSearch-Plus
Not directly comparable
RealWorldQA
Not directly comparable
OmniDocBench 1.5
Not directly comparable
OCRBench V2
Not directly comparable
ODINW13
Not directly comparable
Video-MME (with subtitle)
Not directly comparable
VideoMMMU
Not directly comparable
MLVU (M-Avg)
Not directly comparable
Qwen3.7 Plus has the higher public score, 62.29 versus 40.67, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Qwen3.7 Plus scores higher for coding on the public lane, 53.1 to 26.9. Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Qwen3.7 Plus leads the public agentic tasks lane, 37.7 to 22.2, with Supported evidence for both models and non-overlapping 90% intervals.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Both models list the same context window, 1M.
Last updated September 4, 2026
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