Pareto vs Qwen3.8 2.4T A95B
Too close to call on our weighted score (Qwen3.8 2.4T A95B 34, Pareto 34). The right pick depends on what you value most.
Unbiased
Pareto
34/100- ECI—
- Price$2.50 / $7.50
- Context262K
Alibaba (Qwen)
Qwen3.8 2.4T A95B
34/100- ECI—
- Price$2.00 / $6.00
- Context262K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (Qwen3.8 2.4T A95B 34/100, Pareto 34/100), so choose by what matters most for your work: Qwen3.8 2.4T A95B 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 priceQwen3.8 2.4T A95BQwen3.8 2.4T A95B $3.00 · Pareto $3.75 per 1M tokens (3:1 blend)
- Longest contextAbout the samePareto 262,144 · Qwen3.8 2.4T A95B 262,144 tokens
- Widest inputsParetoPareto: Text, Images · Qwen3.8 2.4T A95B: Text
- Self-hostingQwen3.8 2.4T A95BPublishes downloadable weights (qwen3.8-max)
| Measure | Weight | Pareto | Qwen3.8 2.4T A95B |
|---|---|---|---|
| Price | 50% | 23 | 27 |
| Inputs & features | 30% | 50 | 45 |
| Context window | 20% | 37 | 37 |
| Overall | 100% | 34/100 | 34/100 |
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 | ParetoUnbiased | |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $2.50 | $2.00 (best) |
| Output | $7.50 | $6.00 (best) |
| Cached input | — | — |
| Blended (3:1) | $3.75 | $3.00 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 4 providers | Median of 21 providers |
| Limits | ||
| Context window | 262,144 tokens | 262,144 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Proprietary | Openqwen3.8-max |
| API model ID | — | — |
| API providers | 4 | 21 (best) |
| Released | Sep 17, 2026 | Aug 12, 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.
- Pareto$40.00
Qwen3.8 2.4T A95B$32.00
Which should you choose?
Which is better: Pareto or Qwen3.8 2.4T A95B?
It is close. Our weighted score puts them within a point (Qwen3.8 2.4T A95B 34/100, Pareto 34/100), so choose by what matters most for your work: Qwen3.8 2.4T A95B 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, Pareto or Qwen3.8 2.4T A95B?
Qwen3.8 2.4T A95B is cheaper at $2.00 input / $6.00 output per million tokens (median across 21 API providers). Pareto costs $2.50 input / $7.50 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Qwen3.8 2.4T A95B versus $3.75 for Pareto (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Pareto has not been scored yet and Qwen3.8 2.4T A95B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Pareto and Qwen3.8 2.4T A95B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Pareto and Qwen3.8 2.4T A95B share the same 262,144-token context window. Maximum output per response: Pareto up to 131,072, Qwen3.8 2.4T A95B up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Pareto accepts text and images; Qwen3.8 2.4T A95B accepts text. Pareto handles the widest range of inputs.
Are any of these open source?
Qwen3.8 2.4T A95B publishes its weights (qwen3.8-max) and can be self-hosted; Pareto is proprietary.
Which is newer?
Pareto is the newest, released Sep 17, 2026. Qwen3.8 2.4T A95B came out Aug 12, 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 Oct 4, 2026.