Qwen3.5 9B Base vs Qwen3 Coder Next vs Mercury 2
Too close to call on our weighted score (Mercury 2 52, Qwen3.5 9B Base 50, Qwen3 Coder Next 47). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.5 9B Base
50/100- ECI—
- Price$0.30 / $0.807
- Context262K
- Alibaba (Qwen)
Qwen3 Coder Next
47/100- ECI—
- Price$0.20 / $1.20
- Context262K
InceptionMercury 2
52/100- ECI—
- Price$0.25 / $0.75
- Context128K
Too close to call
It is close. Our weighted score puts them within 2 points (Mercury 2 52/100, Qwen3.5 9B Base 50/100, Qwen3 Coder Next 47/100), 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 Coder Next $0.45 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 9B Base and Qwen3 Coder NextQwen3.5 9B Base 262,144 · Qwen3 Coder Next 262,144 · Mercury 2 128,000 tokens
- Widest inputsQwen3.5 9B BaseQwen3.5 9B Base: Text, Images, Video · Qwen3 Coder Next: Text · Mercury 2: Text
- Self-hostingQwen3.5 9B Base and Qwen3 Coder NextPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3.5 9B Base | Qwen3 Coder Next | Mercury 2 |
|---|---|---|---|---|
| Price | 50% | 65 | 64 | 67 |
| Inputs & features | 30% | 35 | 25 | 45 |
| Context window | 20% | 37 | 37 | 24 |
| Overall | 100% | 50/100 | 47/100 | 52/100 |
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 | Qwen3.5 9B BaseAlibaba (Qwen) | Qwen3 Coder NextAlibaba (Qwen) | Mercury 2Inception |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.20 (best) | $0.25 |
| Output | $0.807 | $1.20 | $0.75 (best) |
| Cached input | — | — | $0.025 |
| Blended (3:1) | $0.427 | $0.45 | $0.375 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 15 providers | Official Inception API |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 128,000 tokens |
| Max output | 65,536 tokens (best) | 65,536 tokens (best) | 50,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | No | No | Yeslow · medium · high |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | — | — | mercury-2 |
| API providers | 1 | 16 (best) | 7 |
| Released | Feb 26, 2026 | Feb 3, 2026 | Feb 24, 2026 |
| Knowledge cutoff | — | Sep 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 9B Base$4.61
- Qwen3 Coder Next$4.40
- Mercury 2$4.00
Which should you choose?
Which is better: Qwen3.5 9B Base, Qwen3 Coder Next or Mercury 2?
It is close. Our weighted score puts them within 2 points (Mercury 2 52/100, Qwen3.5 9B Base 50/100, Qwen3 Coder Next 47/100), 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, Qwen3.5 9B Base, Qwen3 Coder Next or Mercury 2?
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 Coder Next costs $0.20 input / $1.20 output per million tokens (median across 15 API providers). 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 $0.45 for Qwen3 Coder Next (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.5 9B Base has not been scored yet, Qwen3 Coder Next has not been scored yet and Mercury 2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 9B Base, Qwen3 Coder Next and Mercury 2 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 and Qwen3 Coder Next have the largest context windows (262,144 and 262,144 tokens), against 128,000 for Mercury 2. Maximum output per response: Qwen3.5 9B Base up to 65,536, Qwen3 Coder Next up to 65,536, Mercury 2 up to 50,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 9B Base accepts text, images and video; Qwen3 Coder Next accepts text; Mercury 2 accepts text. Qwen3.5 9B Base handles the widest range of inputs.
Are any of these open source?
Qwen3.5 9B Base and Qwen3 Coder Next 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 Coder Next came out Feb 3, 2026. Knowledge cutoff: Qwen3 Coder Next Sep 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.
