Qwen3.5 0.8B vs Qwen3.5 4B vs GPT-5.3 Chat
Too close to call on our weighted score (Qwen3.5 0.8B 57, Qwen3.5 4B 57, GPT-5.3 Chat 40). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.5 0.8B
57/100- ECI—
- Price—
- Context262K
- Alibaba (Qwen)
Qwen3.5 4B
57/100- ECI—
- Price$0.04 / $0.07
- Context262K
OpenAIGPT-5.3 Chat
40/100- ECI—
- Price$1.75 / $14.00
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3.5 0.8B 57/100, Qwen3.5 4B 57/100, GPT-5.3 Chat 40/100), so choose by what matters most for your work: Qwen3.5 4B on price. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3.5 4BQwen3.5 4B $0.048 · GPT-5.3 Chat $4.81 per 1M tokens (3:1 blend) · Qwen3.5 0.8B unpriced
- Longest contextQwen3.5 0.8B and Qwen3.5 4BQwen3.5 0.8B 262,144 · Qwen3.5 4B 262,144 · GPT-5.3 Chat 128,000 tokens
- Widest inputsQwen3.5 0.8B and Qwen3.5 4BQwen3.5 0.8B: Text, Images, Video · Qwen3.5 4B: Text, Images, Video · GPT-5.3 Chat: Text, Images
- Self-hostingQwen3.5 0.8B and Qwen3.5 4BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3.5 0.8B | Qwen3.5 4B | GPT-5.3 Chat |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 70 | 50 |
| Context window | 40% | 37 | 37 | 24 |
| Overall | 100% | 57/100 | 57/100 | 40/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.5 0.8BAlibaba (Qwen) | Qwen3.5 4BAlibaba (Qwen) | GPT-5.3 ChatOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 55.8% | — |
| Price per million tokens | |||
| Input | — | $0.04 (best) | $1.75 |
| Output | — | $0.07 (best) | $14.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.048 (best) | $4.81 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 3 providers | Median of 4 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 128,000 tokens |
| Max output | 81,920 tokens (best) | 81,920 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | OpenApache-2.0 | Proprietary |
| API model ID | — | — | — |
| API providers | 1 | 5 (best) | 4 |
| Released | Mar 2, 2026 | Mar 2, 2026 | Mar 3, 2026 |
| Knowledge cutoff | — | — | Aug 31, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.5 0.8B—
- Qwen3.5 4B$0.54
- GPT-5.3 Chat$45.50
Which should you choose?
Which is better: Qwen3.5 0.8B, Qwen3.5 4B or GPT-5.3 Chat?
It is close. Our weighted score puts them within a point (Qwen3.5 0.8B 57/100, Qwen3.5 4B 57/100, GPT-5.3 Chat 40/100), so choose by what matters most for your work: Qwen3.5 4B on price. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3.5 0.8B, Qwen3.5 4B or GPT-5.3 Chat?
Qwen3.5 4B is cheaper at $0.04 input / $0.07 output per million tokens (median across 3 API providers). GPT-5.3 Chat costs $1.75 input / $14.00 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.048 per million tokens for Qwen3.5 4B versus $4.81 for GPT-5.3 Chat (101× as much). Qwen3.5 0.8B has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.5 0.8B has not been scored yet, Qwen3.5 4B has not been scored yet and GPT-5.3 Chat has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 0.8B, Qwen3.5 4B and GPT-5.3 Chat yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.5 0.8B and Qwen3.5 4B have the largest context windows (262,144 and 262,144 tokens), against 128,000 for GPT-5.3 Chat. Maximum output per response: Qwen3.5 0.8B up to 81,920, Qwen3.5 4B up to 81,920, GPT-5.3 Chat up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 0.8B accepts text, images and video; Qwen3.5 4B accepts text, images and video; GPT-5.3 Chat accepts text and images. Qwen3.5 0.8B handles the widest range of inputs.
Are any of these open source?
Qwen3.5 0.8B and Qwen3.5 4B publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.3 Chat is proprietary.
Which is newer?
GPT-5.3 Chat is the newest, released Mar 3, 2026. Qwen3.5 0.8B came out Mar 2, 2026; Qwen3.5 4B came out Mar 2, 2026. Knowledge cutoff: GPT-5.3 Chat Aug 31, 2025.
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 Nov 2, 2026.
