GPT-5 Nano vs GPT-4.1 mini vs Qwen3.5 9B
Too close to call on our weighted score (Qwen3.5 9B 72, GPT-5 Nano 70, GPT-4.1 mini 60). The right pick depends on what you value most.
OpenAIGPT-5 Nano
70/100- ECI139.4
- Price$0.05 / $0.40
- Context400K
- OpenAI
GPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Alibaba (Qwen)Qwen3.5 9B
72/100- ECI139.5
- Price$0.10 / $0.15
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, GPT-4.1 mini 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and GPT-4.1 mini for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · GPT-5 Nano 139.4 · GPT-4.1 mini 135.0
- Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · GPT-5 Nano $0.138 · GPT-4.1 mini $0.70 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · GPT-5 Nano 400,000 · Qwen3.5 9B 262,144 tokens
- Widest inputsGPT-4.1 mini and Qwen3.5 9BGPT-5 Nano: Text, Images · GPT-4.1 mini: Text, Images, PDFs · Qwen3.5 9B: Text, Images, Video
- Self-hostingQwen3.5 9BPublishes downloadable weights
| Measure | Weight | GPT-5 Nano | GPT-4.1 mini | Qwen3.5 9B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 65 | 59 | 65 |
| Price | 25% | 91 | 57 | 95 |
| Inputs & features | 15% | 70 | 70 | 80 |
| Context window | 10% | 44 | 61 | 37 |
| Overall | 100% | 70/100 | 60/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5 NanoOpenAI | GPT-4.1 miniOpenAI | Qwen3.5 9BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.4 | 135.0 | 139.5 (best) |
| ECI rank | #102 of 148 | #115 of 148 | #101 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 69.4% | 65.9% | 79.0% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 20.0% (best) | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 81.1% (best) | 44.7% | 61.7% |
| SimpleQA VerifiedShort factual questions | 11.7% | 12.7% (best) | — |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.40 | $0.10 |
| Output | $0.40 | $1.60 | $0.15 (best) |
| Cached input | $0.005 (best) | $0.10 | — |
| Blended (3:1) | $0.138 | $0.70 | $0.113 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Median of 14 providers |
| Limits | |||
| Context window | 400,000 tokens | 1,047,576 tokens (best) | 262,144 tokens |
| Max output | 128,000 tokens (best) | 32,768 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yesminimal · low · medium · high | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | gpt-5-nano | gpt-4.1-mini | — |
| API providers | 21 | 24 (best) | 15 |
| Released | Aug 7, 2025 | Apr 14, 2025 | Feb 23, 2026 |
| Knowledge cutoff | May 30, 2024 | Apr 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5 Nano$1.30
- GPT-4.1 mini$7.20
- Qwen3.5 9B$1.30
Which should you choose?
Which is better: GPT-5 Nano, GPT-4.1 mini or Qwen3.5 9B?
It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, GPT-4.1 mini 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and GPT-4.1 mini for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-5 Nano, GPT-4.1 mini or Qwen3.5 9B?
Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). GPT-5 Nano costs $0.05 input / $0.40 output per million tokens (official OpenAI API price); GPT-4.1 mini costs $0.40 input / $1.60 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.138 for GPT-5 Nano (1.2× as much) and $0.70 for GPT-4.1 mini (6.2× as much).
Which scores higher on benchmarks?
Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 of 148), GPT-5 Nano 139.4 (#102 of 148) and GPT-4.1 mini 135.0 (#115 of 148). The confidence ranges of the top two overlap (136.5–141.3 vs 134.9–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, GPT-5 Nano 69.4%, GPT-4.1 mini 65.9%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, Qwen3.5 9B 61.7%, GPT-4.1 mini 44.7%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5 Nano, GPT-4.1 mini and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 400,000 for GPT-5 Nano and 262,144 for Qwen3.5 9B. Maximum output per response: GPT-5 Nano up to 128,000, GPT-4.1 mini up to 32,768, Qwen3.5 9B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-5 Nano accepts text and images; GPT-4.1 mini accepts text, images and PDFs; Qwen3.5 9B accepts text, images and video. GPT-4.1 mini handles the widest range of inputs.
Are any of these open source?
Qwen3.5 9B publishes its weights and can be self-hosted; GPT-5 Nano and GPT-4.1 mini is proprietary.
Which is newer?
Qwen3.5 9B is the newest, released Feb 23, 2026. GPT-5 Nano came out Aug 7, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: GPT-5 Nano May 30, 2024, GPT-4.1 mini Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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