GPT-5 Nano vs Qwen3.7 Plus
At a Glance
| Compare |  GPT-5 NanoOpenAI |  Qwen3.7 PlusQwen |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #46 of 460.0 score · 2/3 sources · provisional · missing LiveBench · full-core range 0.0–33.3 | UnrankedNot in the 46-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.025Openrouter ↗ · Sep 3, 2026 | $0.32Openrouter ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $0.20Openrouter ↗ · Sep 3, 2026 | $1.28Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 400K | 1,000K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | GPT-5 Nano | Qwen3.7-Plus |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,319.7291% of row best · rating · gpt-5-nano-high; 95% CI [1312.87607943, 1326.57003978]; votes 8128; rank 218 | 1,454.20100% of row best · rating · qwen3.7-plus; 95% CI [1449.75378609, 1458.63820942]; votes 39334; rank 39 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,159.1091% of row best · rating · gpt-5-nano-high; 95% CI [1148.05999135, 1170.13906838]; votes 3948; rank 100 | 1,277.81100% of row best · rating · qwen3.7-plus; 95% CI [1270.28208926, 1285.34488566]; votes 10656; rank 31 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 2 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | GPT-5 Nano | Qwen3.7-Plus |
|---|---|---|
| Developer | OpenAI | Qwen |
| Family | Gpt 5 | Qwen3 7 Plus |
| Model | GPT-5 Nano | Qwen3.7-Plus |
| Version | GPT-5 Nano | Qwen3.7-Plus |
| Lifecycle | active | active |
| Released | 2025-08-07 | Unknown |
| Knowledge cutoff | 2024-05-31 | Unknown |
| Input modalities | Text, Image | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 400K | 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), Fireworks Ai (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | agents, chat, computer-use, reasoning, structured_outputs, tools, vision |
GPT-5 Nano Capabilities
Qwen3.7 Plus Capabilities
Related Comparisons
All image comparisons →| A | Pair | B | Context |
|---|---|---|---|
GPT-5 NanoOpenAI | vs | GPT-6 AstraOpenAI | family variantsimage, text |
Claude Fable 5.1Anthropic | vs | GPT-5 NanoOpenAI | cross-developer peersimage, text |
 Gemini 3.1 ProGoogle DeepMind | vs | GPT-5 NanoOpenAI | cross-developer peerstext |
 DeepSeek-V4.1-FlashDeepSeek | vs | GPT-5 NanoOpenAI | cross-developer peersimage, text |
GPT-5 NanoOpenAI | vs | Grok 4.6xAI | cross-developer peersimage, text |
GPT-5 NanoOpenAI | vs | Qwen3.8-MaxQwen | cross-developer peersimage, text |
 Kimi-K3Moonshot AI | vs | GPT-5 NanoOpenAI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | GPT-5 NanoOpenAI | cross-developer peersimage, text |
GPT-5 NanoOpenAI | vs |  GLM-5.3Z.ai | cross-developer peerstext |
GPT-5 NanoOpenAI | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | GPT-5 NanoOpenAI | cross-developer peersimage, text |
 Mistral Large 3Mistral AI | vs | GPT-5 NanoOpenAI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
GPT-5 Nano vs Qwen3.7 Plus FAQs
Is GPT-5 Nano or Qwen3.7 Plus better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5 Nano and Qwen3.7 Plus, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-5 Nano or Qwen3.7 Plus?+
GPT-5 Nano is $0.025 and Qwen3.7 Plus is $0.32 per million tokens, so GPT-5 Nano is cheaper on this metric. GPT-5 Nano is $0.20 and Qwen3.7 Plus is $1.28 per million tokens, so GPT-5 Nano is cheaper on this metric.
Which has a larger context window, GPT-5 Nano or Qwen3.7 Plus?+
Qwen3.7 Plus has the larger sourced context window. GPT-5 Nano supports 400K and Qwen3.7 Plus supports 1,000K.
Which performs better in benchmarks, GPT-5 Nano or Qwen3.7 Plus?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can GPT-5 Nano or Qwen3.7 Plus be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. GPT-5 Nano is not marked open weight; Qwen3.7 Plus is not marked open weight.
Can GPT-5 Nano and Qwen3.7 Plus understand images?+
GPT-5 Nano is documented with image input; Qwen3.7 Plus is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-5 Nano or Qwen3.7 Plus?+
Qwen3.7 Plus has the larger sourced maximum output: GPT-5 Nano supports 128K and Qwen3.7 Plus supports 131K output tokens.
Do GPT-5 Nano and Qwen3.7 Plus support reasoning and tool use?+
GPT-5 Nano: reasoning, tool calling, and image input. Qwen3.7 Plus: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-5 Nano or Qwen3.7 Plus?+
GPT-5 Nano has 2 sourced provider routes; Qwen3.7 Plus has 4, so Qwen3.7 Plus has broader tracked availability.
Which offers better value, GPT-5 Nano or Qwen3.7 Plus?+
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.