Multimodal
Like-for-like- Inkling-Small
- 76.6
- Qwen3.7 Plus
- 81.5
- Weighted basis
- 2 vs 2 rows
- Reading
- Qwen3.7 Plus leads
Model comparison
Updated July 30, 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.
14 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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are 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.
5 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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 | Inkling-Small | Qwen3.7 Plus | Weighted basis | Reading |
|---|---|---|---|---|
| Multimodal | 76.6 | 81.5 | Like-for-like2 vs 2 rows | Qwen3.7 Plus leads |
| Agentic | 70.1 | 71.7 | Directional only2 vs 2 rows | Directional only |
| Coding | 62.4 | 75.6 | Directional only3 vs 4 rows | Directional only |
| Knowledge | 53.4 | 60.1 | Directional only2 vs 4 rows | Directional only |
| Math | 92.9 | 92.9 | Directional only2 vs 1 rows | Directional only |
| Instruction following | 82.2 | 84.5 | Directional only1 vs 2 rows | Directional only |
| Reasoning | 40.1 | 91.7 | Not comparable1 vs 1 rows | Not comparable |
| Multilingual | Not measured | 85.4 | Not comparable0 vs 1 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.
HLE
Knowledge
Terminal-Bench 2.0
Agentic
MMMU-Pro
Multimodal
CharXiv
Multimodal
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
Qwen3.7 Plus has no comparable published API token rate.
50K fresh input + 3K output tokens
Qwen3.7 Plus has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
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.
Inkling-Small
1M
Qwen3.7 Plus
1M
Inkling-Small
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.
Inkling-Small
$0.116 per 1M cached input tokens
Qwen3.7 Plus
No comparable hosted API rate
Inkling-Small
Not sourced
Qwen3.7 Plus
Not sourced
Inkling-Small
Not sourced
Qwen3.7 Plus
Not sourced
Inkling-Small
Not sourced
Qwen3.7 Plus
Not sourced
Inkling-Small
Hybrid
Qwen3.7 Plus
Reasoning
Inkling-Small
Open Weight
Qwen3.7 Plus
Proprietary
Inkling-Small
Open Weight
Qwen3.7 Plus
Proprietary
Inkling-Small
2026-07-30
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
BrowseComp
Not directly comparable
MCP Atlas
Inkling-Small leads this result
Toolathlon-Verified
Not directly comparable
QwenClawBench
Not directly comparable
Claw-Eval
Not directly comparable
BFCL v4
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
Inkling-Small leads this result
SWE-bench Pro
Qwen3.7 Plus leads this result
Terminal-Bench 2.0
Qwen3.7 Plus leads this result
SciCode
Qwen3.7 Plus leads this result
SWE Multilingual
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
Inkling-Small leads this result
HLE w/o tools
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
MMMU-Pro
Qwen3.7 Plus leads this result
CharXiv
Qwen3.7 Plus leads this result
CharXiv w/o tools
Not directly comparable
MathVision
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
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 current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
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 July 30, 2026
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.