Qwen3.5 0.8B vs MiMo-V2-Pro vs GPT-5.3 Chat
Qwen3.5 0.8B comes out ahead, 57 to 45 and 40 on our weighted score.
- Our pick
Alibaba (Qwen)Qwen3.5 0.8B
57/100- ECI—
- Price—
- Context262K
XiaomiMiMo-V2-Pro
45/100- ECI—
- Price$1.00 / $3.00
- Context1.05M
OpenAIGPT-5.3 Chat
40/100- ECI—
- Price$1.75 / $14.00
- Context128K
Qwen3.5 0.8B is our pick
Qwen3.5 0.8B is the better all-round choice, scoring 57/100 against MiMo-V2-Pro (45) and GPT-5.3 Chat (40). It leads on inputs & features. MiMo-V2-Pro wins on context window. 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 priceMiMo-V2-ProMiMo-V2-Pro $1.50 · GPT-5.3 Chat $4.81 per 1M tokens (3:1 blend) · Qwen3.5 0.8B unpriced
- Longest contextMiMo-V2-ProMiMo-V2-Pro 1,048,576 · Qwen3.5 0.8B 262,144 · GPT-5.3 Chat 128,000 tokens
- Widest inputsQwen3.5 0.8BQwen3.5 0.8B: Text, Images, Video · MiMo-V2-Pro: Text · GPT-5.3 Chat: Text, Images
- Self-hostingQwen3.5 0.8BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3.5 0.8B | MiMo-V2-Pro | GPT-5.3 Chat |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 35 | 50 |
| Context window | 40% | 37 | 61 | 24 |
| Overall | 100% | 57/100 | 45/100 | 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) | MiMo-V2-ProXiaomi | GPT-5.3 ChatOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $1.00 (best) | $1.75 |
| Output | — | $3.00 (best) | $14.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $1.50 (best) | $4.81 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 1 providers | Median of 4 providers |
| Limits | |||
| Context window | 262,144 tokens | 1,048,576 tokens (best) | 128,000 tokens |
| Max output | 81,920 tokens | 131,072 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Proprietary |
| API model ID | — | — | — |
| API providers | 1 | 2 | 4 (best) |
| Released | Mar 2, 2026 | Mar 18, 2026 | Mar 3, 2026 |
| Knowledge cutoff | — | Dec 2024 | 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—
- MiMo-V2-Pro$16.00
- GPT-5.3 Chat$45.50
Which should you choose?
Which is better: Qwen3.5 0.8B, MiMo-V2-Pro or GPT-5.3 Chat?
Qwen3.5 0.8B is the better all-round choice, scoring 57/100 against MiMo-V2-Pro (45) and GPT-5.3 Chat (40). It leads on inputs & features. MiMo-V2-Pro wins on context window. 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, MiMo-V2-Pro or GPT-5.3 Chat?
MiMo-V2-Pro is cheaper at $1.00 input / $3.00 output per million tokens (median across 1 API provider). 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 $1.50 per million tokens for MiMo-V2-Pro versus $4.81 for GPT-5.3 Chat (3.2× 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, MiMo-V2-Pro 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, MiMo-V2-Pro 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?
MiMo-V2-Pro has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.5 0.8B and 128,000 for GPT-5.3 Chat. Maximum output per response: Qwen3.5 0.8B up to 81,920, MiMo-V2-Pro up to 131,072, 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; MiMo-V2-Pro accepts text; 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 publishes its weights (Apache-2.0) and can be self-hosted; MiMo-V2-Pro and GPT-5.3 Chat is proprietary.
Which is newer?
MiMo-V2-Pro is the newest, released Mar 18, 2026. GPT-5.3 Chat came out Mar 3, 2026; Qwen3.5 0.8B came out Mar 2, 2026. Knowledge cutoff: MiMo-V2-Pro Dec 2024, 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.
