GPT-5.3 Chat vs Mercury 2 vs Qwen3.5 9B Base
Too close to call on our weighted score (Mercury 2 52, Qwen3.5 9B Base 50, GPT-5.3 Chat 28). The right pick depends on what you value most.
OpenAIGPT-5.3 Chat
28/100- ECI—
- Price$1.75 / $14.00
- Context128K
InceptionMercury 2
52/100- ECI—
- Price$0.25 / $0.75
- Context128K
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 (Mercury 2 52/100, Qwen3.5 9B Base 50/100, GPT-5.3 Chat 28/100), so choose by what matters most for your work: Mercury 2 on price and Qwen3.5 9B Base for long inputs. 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 · GPT-5.3 Chat $4.81 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 9B BaseQwen3.5 9B Base 262,144 · GPT-5.3 Chat 128,000 · Mercury 2 128,000 tokens
- Widest inputsQwen3.5 9B BaseGPT-5.3 Chat: Text, Images · Mercury 2: Text · Qwen3.5 9B Base: Text, Images, Video
- Self-hostingQwen3.5 9B BasePublishes downloadable weights (Apache-2.0)
| Measure | Weight | GPT-5.3 Chat | Mercury 2 | Qwen3.5 9B Base |
|---|---|---|---|---|
| Price | 50% | 17 | 67 | 65 |
| Inputs & features | 30% | 50 | 45 | 35 |
| Context window | 20% | 24 | 24 | 37 |
| Overall | 100% | 28/100 | 52/100 | 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 | GPT-5.3 ChatOpenAI | Mercury 2Inception | Qwen3.5 9B BaseAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.75 | $0.25 (best) | $0.30 |
| Output | $14.00 | $0.75 (best) | $0.807 |
| Cached input | — | $0.025 | — |
| Blended (3:1) | $4.81 | $0.375 (best) | $0.427 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official Inception API | Median of 1 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 16,384 tokens | 50,000 tokens | 65,536 tokens (best) |
| 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 | Yeslow · medium · high | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenApache-2.0 |
| API model ID | — | mercury-2 | — |
| API providers | 4 | 7 (best) | 1 |
| Released | Mar 3, 2026 | Feb 24, 2026 | Feb 26, 2026 |
| Knowledge cutoff | 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.
- GPT-5.3 Chat$45.50
- Mercury 2$4.00
- Qwen3.5 9B Base$4.61
Which should you choose?
Which is better: GPT-5.3 Chat, Mercury 2 or Qwen3.5 9B Base?
It is close. Our weighted score puts them within 2 points (Mercury 2 52/100, Qwen3.5 9B Base 50/100, GPT-5.3 Chat 28/100), so choose by what matters most for your work: Mercury 2 on price and Qwen3.5 9B Base for long inputs. 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, GPT-5.3 Chat, Mercury 2 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); 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 $0.375 per million tokens for Mercury 2 versus $0.427 for Qwen3.5 9B Base (1.1× as much) and $4.81 for GPT-5.3 Chat (13× as much).
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, Mercury 2 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 GPT-5.3 Chat, Mercury 2 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 128,000 for GPT-5.3 Chat and 128,000 for Mercury 2. Maximum output per response: GPT-5.3 Chat up to 16,384, Mercury 2 up to 50,000, Qwen3.5 9B Base up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-5.3 Chat accepts text and images; Mercury 2 accepts text; 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?
Qwen3.5 9B Base publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.3 Chat and Mercury 2 is proprietary.
Which is newer?
GPT-5.3 Chat is the newest, released Mar 3, 2026. Qwen3.5 9B Base came out Feb 26, 2026; Mercury 2 came out Feb 24, 2026. Knowledge cutoff: 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.
