Qwen-MT Plus vs Step 1 (32K) vs Sonar Deep Research
Too close to call on our weighted score (Sonar Deep Research 20, Step 1 (32K) 18, Qwen-MT Plus 12). The right pick depends on what you value most.
Alibaba (Qwen)Qwen-MT Plus
12/100- ECI—
- Price$2.46 / $7.37
- Context16K
StepFunStep 1 (32K)
18/100- ECI—
- Price$2.05 / $9.59
- Context33K
PerplexitySonar Deep Research
20/100- ECI—
- Price$2.00 / $8.00
- Context128K
Too close to call
It is close. Our weighted score puts them within 1 points (Sonar Deep Research 20/100, Step 1 (32K) 18/100, Qwen-MT Plus 12/100), so choose by what matters most for your work: Sonar Deep Research on price and Sonar Deep Research 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 priceSonar Deep ResearchSonar Deep Research $3.50 · Qwen-MT Plus $3.69 · Step 1 (32K) $3.94 per 1M tokens (3:1 blend)
- Longest contextSonar Deep ResearchSonar Deep Research 128,000 · Step 1 (32K) 32,768 · Qwen-MT Plus 16,384 tokens
- Widest inputsSame inputsQwen-MT Plus: Text · Step 1 (32K): Text · Sonar Deep Research: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Qwen-MT Plus | Step 1 (32K) | Sonar Deep Research |
|---|---|---|---|---|
| Price | 50% | 23 | 22 | 24 |
| Inputs & features | 30% | 0 | 25 | 10 |
| Context window | 20% | 0 | 0 | 24 |
| Overall | 100% | 12/100 | 18/100 | 20/100 |
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 | Qwen-MT PlusAlibaba (Qwen) | Step 1 (32K)StepFun | Sonar Deep ResearchPerplexity |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.46 | $2.05 | $2.00 (best) |
| Output | $7.37 (best) | $9.59 | $8.00 |
| Cached input | — | $0.41 | — |
| Blended (3:1) | $3.69 | $3.94 | $3.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official StepFun (Global) API | Official Perplexity API |
| Limits | |||
| Context window | 16,384 tokens | 32,768 tokens | 128,000 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens (best) | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yesminimal · low · medium · high |
| Tool calling | No | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | qwen-mt-plus | step-1-32k | sonar-deep-research |
| API providers | 1 | 1 | 3 (best) |
| Released | Jan 2025 | Jan 1, 2025 | Feb 1, 2025 |
| Knowledge cutoff | Apr 2024 | Jun 2024 | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen-MT Plus$39.34
- Step 1 (32K)$39.68
- Sonar Deep Research$36.00
Which should you choose?
Which is better: Qwen-MT Plus, Step 1 (32K) or Sonar Deep Research?
It is close. Our weighted score puts them within 1 points (Sonar Deep Research 20/100, Step 1 (32K) 18/100, Qwen-MT Plus 12/100), so choose by what matters most for your work: Sonar Deep Research on price and Sonar Deep Research 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, Qwen-MT Plus, Step 1 (32K) or Sonar Deep Research?
Sonar Deep Research is cheaper at $2.00 input / $8.00 output per million tokens (official Perplexity API price). Qwen-MT Plus costs $2.46 input / $7.37 output per million tokens (official Alibaba API price); Step 1 (32K) costs $2.05 input / $9.59 output per million tokens (official StepFun (Global) API price). At a typical mix of three input tokens to one output token, that is $3.50 per million tokens for Sonar Deep Research versus $3.69 for Qwen-MT Plus (1.1× as much) and $3.94 for Step 1 (32K) (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen-MT Plus has not been scored yet, Step 1 (32K) has not been scored yet and Sonar Deep Research has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen-MT Plus, Step 1 (32K) and Sonar Deep Research yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-MT Plus and Sonar Deep Research does not support tool calling, which most coding agents need.
Which has the bigger context window?
Sonar Deep Research has the largest context window at 128,000 tokens, against 32,768 for Step 1 (32K) and 16,384 for Qwen-MT Plus. Maximum output per response: Qwen-MT Plus up to 8,192, Step 1 (32K) up to 32,768, Sonar Deep Research up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen-MT Plus accepts text; Step 1 (32K) accepts text; Sonar Deep Research accepts text. They handle the same number of input types.
Are any of these open source?
No. Qwen-MT Plus, Step 1 (32K) and Sonar Deep Research are proprietary and only available through APIs and apps.
Which is newer?
Sonar Deep Research is the newest, released Feb 1, 2025. Qwen-MT Plus came out Jan 2025; Step 1 (32K) came out Jan 1, 2025. Knowledge cutoff: Qwen-MT Plus Apr 2024, Step 1 (32K) Jun 2024, Sonar Deep Research Jan 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 Oct 4, 2026.
