Apertus 70B vs Qwen3-Next 80B-A3B (Thinking)
Too close to call on our weighted score (Qwen3-Next 80B-A3B (Thinking) 34, Apertus 70B 33). The right pick depends on what you value most.
Swiss AI
Apertus 70B
33/100- ECI—
- Price$0.82 / $2.42
- Context66K
Alibaba (Qwen)Qwen3-Next 80B-A3B (Thinking)
34/100- ECI—
- Price$0.50 / $6.00
- Context131K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 1 points (Qwen3-Next 80B-A3B (Thinking) 34/100, Apertus 70B 33/100), so choose by what matters most for your work: Apertus 70B on price and Qwen3-Next 80B-A3B (Thinking) 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 priceApertus 70BApertus 70B $1.22 · Qwen3-Next 80B-A3B (Thinking) $1.88 per 1M tokens (3:1 blend)
- Longest contextQwen3-Next 80B-A3B (Thinking)Qwen3-Next 80B-A3B (Thinking) 131,072 · Apertus 70B 65,536 tokens
- Widest inputsSame inputsApertus 70B: Text · Qwen3-Next 80B-A3B (Thinking): Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Apertus 70B | Qwen3-Next 80B-A3B (Thinking) |
|---|---|---|---|
| Price | 50% | 46 | 37 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 12 | 24 |
| Overall | 100% | 33/100 | 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 | Apertus 70BSwiss AI | Qwen3-Next 80B-A3B (Thinking)Alibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.82 | $0.50 (best) |
| Output | $2.42 (best) | $6.00 |
| Cached input | — | — |
| Blended (3:1) | $1.22 (best) | $1.88 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Alibaba API |
| Limits | ||
| Context window | 65,536 tokens | 131,072 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache-2.0 | Open |
| API model ID | — | qwen3-next-80b-a3b-thinking |
| API providers | 3 | 10 (best) |
| Released | Sep 2, 2025 | Sep 2025 |
| Knowledge cutoff | Sep 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Apertus 70B$13.04
- Qwen3-Next 80B-A3B (Thinking)$17.00
Which should you choose?
Which is better: Apertus 70B or Qwen3-Next 80B-A3B (Thinking)?
It is close. Our weighted score puts them within 1 points (Qwen3-Next 80B-A3B (Thinking) 34/100, Apertus 70B 33/100), so choose by what matters most for your work: Apertus 70B on price and Qwen3-Next 80B-A3B (Thinking) 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, Apertus 70B or Qwen3-Next 80B-A3B (Thinking)?
Apertus 70B is cheaper at $0.82 input / $2.42 output per million tokens (median across 3 API providers). Qwen3-Next 80B-A3B (Thinking) costs $0.50 input / $6.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.22 per million tokens for Apertus 70B versus $1.88 for Qwen3-Next 80B-A3B (Thinking) (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Apertus 70B has not been scored yet and Qwen3-Next 80B-A3B (Thinking) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Apertus 70B and Qwen3-Next 80B-A3B (Thinking) 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?
Qwen3-Next 80B-A3B (Thinking) has the largest context window at 131,072 tokens, against 65,536 for Apertus 70B. Maximum output per response: Apertus 70B up to 8,192, Qwen3-Next 80B-A3B (Thinking) up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Apertus 70B accepts text; Qwen3-Next 80B-A3B (Thinking) accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Apertus 70B is the newest, released Sep 2, 2025. Qwen3-Next 80B-A3B (Thinking) came out Sep 2025. Knowledge cutoff: Apertus 70B Sep 2025, Qwen3-Next 80B-A3B (Thinking) Apr 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.
Related comparisons
- Add Qwen3 VL 235B A22B ThinkingThree-way comparison
- Apertus 70B vs Qwen3 VL 235B A22B ThinkingAlibaba (Qwen)
- Apertus 70B vs GLM-4.6Z.ai (Zhipu)
- Apertus 70B vs Ling-1TinclusionAI
- Apertus 70B vs Mistral Medium 3.1Mistral AI
- Qwen3-Next 80B-A3B (Thinking) vs Palmyra X5Writer
- Qwen3-Next 80B-A3B (Thinking) vs GPT-5-CodexOpenAI
