Mercury 2 vs Qwen3.5 122B-A10B vs Qwen3.5 9B Base
Too close to call on our weighted score (Qwen3.5 122B-A10B 54, Mercury 2 52, Qwen3.5 9B Base 50). The right pick depends on what you value most.
InceptionMercury 2
52/100- ECI—
- Price$0.25 / $0.75
- Context128K
Alibaba (Qwen)Qwen3.5 122B-A10B
54/100- ECI—
- Price$0.40 / $3.20
- Context262K
- Alibaba (Qwen)
Qwen3.5 9B Base
50/100- ECI—
- Price$0.30 / $0.807
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Qwen3.5 122B-A10B 54/100, Mercury 2 52/100, Qwen3.5 9B Base 50/100), so choose by what matters most for your work: Mercury 2 on price. 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 priceMercury 2Mercury 2 $0.375 · Qwen3.5 9B Base $0.427 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10B and Qwen3.5 9B BaseQwen3.5 122B-A10B 262,144 · Qwen3.5 9B Base 262,144 · Mercury 2 128,000 tokens
- Widest inputsQwen3.5 122B-A10B and Qwen3.5 9B BaseMercury 2: Text · Qwen3.5 122B-A10B: Text, Images, Video · Qwen3.5 9B Base: Text, Images, Video
- Self-hostingQwen3.5 122B-A10B and Qwen3.5 9B BasePublishes downloadable weights (Apache-2.0)
| Measure | Weight | Mercury 2 | Qwen3.5 122B-A10B | Qwen3.5 9B Base |
|---|---|---|---|---|
| Price | 50% | 67 | 46 | 65 |
| Inputs & features | 30% | 45 | 80 | 35 |
| Context window | 20% | 24 | 37 | 37 |
| Overall | 100% | 52/100 | 54/100 | 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 | Qwen3.5 122B-A10BAlibaba (Qwen) | Qwen3.5 9B BaseAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.25 (best) | $0.40 | $0.30 |
| Output | $0.75 (best) | $3.20 | $0.807 |
| Cached input | $0.025 | — | — |
| Blended (3:1) | $0.375 (best) | $1.10 | $0.427 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Inception API | Official Alibaba API | Median of 1 providers |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 50,000 tokens | 65,536 tokens (best) | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · medium · high | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | OpenApache-2.0 |
| API model ID | mercury-2 | qwen3.5-122b-a10b | — |
| API providers | 7 | 22 (best) | 1 |
| Released | Feb 24, 2026 | Feb 23, 2026 | Feb 26, 2026 |
| Knowledge cutoff | — | — | — |
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
- Qwen3.5 122B-A10B$10.40
- Qwen3.5 9B Base$4.61
Which should you choose?
Which is better: Mercury 2, Qwen3.5 122B-A10B or Qwen3.5 9B Base?
It is close. Our weighted score puts them within 2 points (Qwen3.5 122B-A10B 54/100, Mercury 2 52/100, Qwen3.5 9B Base 50/100), so choose by what matters most for your work: Mercury 2 on price. 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, Qwen3.5 122B-A10B or Qwen3.5 9B Base?
Mercury 2 is cheaper at $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); Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.375 per million tokens for Mercury 2 versus $0.427 for Qwen3.5 9B Base (1.1× as much) and $1.10 for Qwen3.5 122B-A10B (2.9× 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, Qwen3.5 122B-A10B 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, Qwen3.5 122B-A10B 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 122B-A10B and Qwen3.5 9B Base have the largest context windows (262,144 and 262,144 tokens), against 128,000 for Mercury 2. Maximum output per response: Mercury 2 up to 50,000, Qwen3.5 122B-A10B up to 65,536, Qwen3.5 9B Base up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Mercury 2 accepts text; Qwen3.5 122B-A10B accepts text, images and video; Qwen3.5 9B Base accepts text, images and video. Qwen3.5 122B-A10B handles the widest range of inputs.
Are any of these open source?
Qwen3.5 122B-A10B and Qwen3.5 9B Base publishes its weights (Apache-2.0) and can be self-hosted; Mercury 2 is proprietary.
Which is newer?
Qwen3.5 9B Base is the newest, released Feb 26, 2026. Mercury 2 came out Feb 24, 2026; Qwen3.5 122B-A10B came out Feb 23, 2026.
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.
