Mercury 2 vs Mistral Small 4 vs Qwen3.5 9B Base
Mistral Small 4 comes out ahead, 65 to 52 and 50 on our weighted score, and it is the cheaper option too.
InceptionMercury 2
52/100- ECI—
- Price$0.25 / $0.75
- Context128K
- Our pick
Mistral AIMistral Small 4
65/100- ECI—
- Price$0.15 / $0.60
- Context256K
Alibaba (Qwen)Qwen3.5 9B Base
50/100- ECI—
- Price$0.30 / $0.807
- Context262K
Mistral Small 4 is our pick
Mistral Small 4 is the better all-round choice, scoring 65/100 against Mercury 2 (52) and Qwen3.5 9B Base (50). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceMistral Small 4Mistral Small 4 $0.263 · Mercury 2 $0.375 · Qwen3.5 9B Base $0.427 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 9B BaseQwen3.5 9B Base 262,144 · Mistral Small 4 256,000 · Mercury 2 128,000 tokens
- Widest inputsQwen3.5 9B BaseMercury 2: Text · Mistral Small 4: Text, Images · Qwen3.5 9B Base: Text, Images, Video
- Self-hostingMistral Small 4 and Qwen3.5 9B BasePublishes downloadable weights (Apache-2.0)
| Measure | Weight | Mercury 2 | Mistral Small 4 | Qwen3.5 9B Base |
|---|---|---|---|---|
| Price | 50% | 67 | 74 | 65 |
| Inputs & features | 30% | 45 | 70 | 35 |
| Context window | 20% | 24 | 36 | 37 |
| Overall | 100% | 52/100 | 65/100 | 50/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mercury 2Inception | Mistral Small 4Mistral AI | Qwen3.5 9B BaseAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.25 | $0.15 (best) | $0.30 |
| Output | $0.75 | $0.60 (best) | $0.807 |
| Cached input | $0.025 | $0.015 (best) | — |
| Blended (3:1) | $0.375 | $0.263 (best) | $0.427 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Inception API | Official Mistral API | Median of 1 providers |
| Limits | |||
| Context window | 128,000 tokens | 256,000 tokens | 262,144 tokens (best) |
| Max output | 50,000 tokens | 256,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high | Yeshigh | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | OpenApache-2.0 |
| API model ID | mercury-2 | mistral-small-2603 | — |
| API providers | 7 | 21 (best) | 1 |
| Released | Feb 24, 2026 | Mar 16, 2026 | Feb 26, 2026 |
| Knowledge cutoff | — | Jun 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mercury 2$4.00
- Mistral Small 4$2.70
- Qwen3.5 9B Base$4.61
Which should you choose?
Which is better: Mercury 2, Mistral Small 4 or Qwen3.5 9B Base?
Mistral Small 4 is the better all-round choice, scoring 65/100 against Mercury 2 (52) and Qwen3.5 9B Base (50). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Mercury 2, Mistral Small 4 or Qwen3.5 9B Base?
Mistral Small 4 is cheaper at $0.15 input / $0.60 output per million tokens (official Mistral API price). Mercury 2 costs $0.25 input / $0.75 output per million tokens (official Inception API price); Qwen3.5 9B Base costs $0.30 input / $0.807 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for Mistral Small 4 versus $0.375 for Mercury 2 (1.4× as much) and $0.427 for Qwen3.5 9B Base (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mercury 2 has not been scored yet, Mistral Small 4 has not been scored yet and Qwen3.5 9B Base has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mercury 2, Mistral Small 4 and Qwen3.5 9B Base yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen3.5 9B Base does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3.5 9B Base has the largest context window at 262,144 tokens, against 256,000 for Mistral Small 4 and 128,000 for Mercury 2. Maximum output per response: Mercury 2 up to 50,000, Mistral Small 4 up to 256,000, Qwen3.5 9B Base up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Mercury 2 accepts text; Mistral Small 4 accepts text and images; Qwen3.5 9B Base accepts text, images and video. Qwen3.5 9B Base handles the widest range of inputs.
Are any of these open source?
Mistral Small 4 and Qwen3.5 9B Base publishes its weights (Apache-2.0) and can be self-hosted; Mercury 2 is proprietary.
Which is newer?
Mistral Small 4 is the newest, released Mar 16, 2026. Qwen3.5 9B Base came out Feb 26, 2026; Mercury 2 came out Feb 24, 2026. Knowledge cutoff: Mistral Small 4 Jun 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.
