GPT-5.6 Sol vs Qwen3.7 Flash
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | GPT-5.6 Sol | Qwen3.7 Flash |
|---|---|---|
| IntelligenceHigher is better · MM Intelligence v1.2 | #4 of 2285.2 score | UnrankedNot in the 22-model eligible cohort |
| CostLower is better · Published-token output estimate | #20 of 36$0.117 per LiveBench case | UnrankedNot in the 36-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.0 | #3 of 2263.6 score | UnrankedNot in the 22-model eligible cohort |
Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | GPT-5.6 Sol | Qwen3.7 Flash |
|---|---|---|
| Developer | OpenAI | Qwen |
| Family | Gpt 5 6 | Qwen3 7 |
| Model | GPT-5.6 Sol | Qwen3.7 Flash |
| Version | GPT-5.6 Sol | Qwen3.7 Flash |
| Lifecycle | active | active |
| Released | Unknown | 2026-07-15 |
| Knowledge cutoff | 2026-02-16 | Unknown |
| Input modalities | Text, Image | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 1,050K | 1,000K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Openai (Standard), Openrouter (Standard) | Alibaba Cloud Model Studio (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, generation, reasoning, structured_outputs, tools, vision |
13 comparable fields · 8 material differences · Pair passes the primary-source comparison gate
GPT-5.6 Sol Capabilities
Qwen3.7 Flash Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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Primary Evidence
Sources and Freshness
Questions
GPT-5.6 Sol vs Qwen3.7 Flash FAQs
Is GPT-5.6 Sol or Qwen3.7 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5.6 Sol and Qwen3.7 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-5.6 Sol or Qwen3.7 Flash?+
GPT-5.6 Sol is $2.00 and Qwen3.7 Flash is $0.030 per million tokens, so Qwen3.7 Flash is cheaper on this metric. GPT-5.6 Sol is $10.00 and Qwen3.7 Flash is $0.13 per million tokens, so Qwen3.7 Flash is cheaper on this metric.
Which has a larger context window, GPT-5.6 Sol or Qwen3.7 Flash?+
GPT-5.6 Sol has the larger sourced context window. GPT-5.6 Sol supports 1,050K and Qwen3.7 Flash supports 1,000K.
Which performs better in benchmarks, GPT-5.6 Sol or Qwen3.7 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can GPT-5.6 Sol or Qwen3.7 Flash be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. GPT-5.6 Sol is not marked open weight; Qwen3.7 Flash is not marked open weight.
Can GPT-5.6 Sol and Qwen3.7 Flash understand images?+
GPT-5.6 Sol is documented with image input; Qwen3.7 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-5.6 Sol or Qwen3.7 Flash?+
GPT-5.6 Sol has the larger sourced maximum output: GPT-5.6 Sol supports 128K and Qwen3.7 Flash supports 66K output tokens.
Do GPT-5.6 Sol and Qwen3.7 Flash support reasoning and tool use?+
GPT-5.6 Sol: reasoning, tool calling, and image input. Qwen3.7 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-5.6 Sol or Qwen3.7 Flash?+
GPT-5.6 Sol has 2 sourced provider routes; Qwen3.7 Flash has 2, a tie.
Which offers better value, GPT-5.6 Sol or Qwen3.7 Flash?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.