GPT-5.3 Chat vs MiMo-V2-Pro vs Qwen3.5 0.8B
Qwen3.5 0.8B comes out ahead, 57 to 45 and 40 on our weighted score.
OpenAIGPT-5.3 Chat
40/100- ECI—
- Price$1.75 / $14.00
- Context128K
XiaomiMiMo-V2-Pro
45/100- ECI—
- Price$1.00 / $3.00
- Context1.05M
- Our pick
Alibaba (Qwen)Qwen3.5 0.8B
57/100- ECI—
- Price—
- Context262K
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 0.8BGPT-5.3 Chat: Text, Images · MiMo-V2-Pro: Text · Qwen3.5 0.8B: Text, Images, Video
- Self-hostingQwen3.5 0.8BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | GPT-5.3 Chat | MiMo-V2-Pro | Qwen3.5 0.8B |
|---|---|---|---|---|
| Inputs & features | 60% | 50 | 35 | 70 |
| Context window | 40% | 24 | 61 | 37 |
| Overall | 100% | 40/100 | 45/100 | 57/100 |
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 | GPT-5.3 ChatOpenAI | MiMo-V2-ProXiaomi | Qwen3.5 0.8BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.75 | $1.00 (best) | — |
| Output | $14.00 | $3.00 (best) | — |
| Cached input | — | — | — |
| Blended (3:1) | $4.81 | $1.50 (best) | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 4 providers | Median of 1 providers | — |
| Limits | |||
| Context window | 128,000 tokens | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | 16,384 tokens | 131,072 tokens (best) | 81,920 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenApache-2.0 |
| API model ID | — | — | — |
| API providers | 4 (best) | 2 | 1 |
| Released | Mar 3, 2026 | Mar 18, 2026 | Mar 2, 2026 |
| Knowledge cutoff | Aug 31, 2025 | Dec 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-5.3 Chat$45.50
- MiMo-V2-Pro$16.00
- Qwen3.5 0.8B—
Which should you choose?
Which is better: GPT-5.3 Chat, MiMo-V2-Pro or Qwen3.5 0.8B?
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, GPT-5.3 Chat, MiMo-V2-Pro or Qwen3.5 0.8B?
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. GPT-5.3 Chat has not been scored yet, MiMo-V2-Pro has not been scored yet and Qwen3.5 0.8B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.3 Chat, MiMo-V2-Pro and Qwen3.5 0.8B 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: GPT-5.3 Chat up to 16,384, MiMo-V2-Pro up to 131,072, Qwen3.5 0.8B up to 81,920 tokens.
Which can read images, PDFs, audio or video?
GPT-5.3 Chat accepts text and images; MiMo-V2-Pro accepts text; Qwen3.5 0.8B accepts text, images and video. 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; GPT-5.3 Chat and MiMo-V2-Pro 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: GPT-5.3 Chat Aug 31, 2025, MiMo-V2-Pro Dec 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 Nov 2, 2026.
