Apertus 70B vs QVQ Max vs Qwen3-Next 80B-A3B (Thinking)
QVQ Max comes out ahead, 40 to 34 and 33 on our weighted score, though Apertus 70B is 42% cheaper per token.
Swiss AI
Apertus 70B
33/100- ECI—
- Price$0.82 / $2.42
- Context66K
- Our pick
Alibaba (Qwen)QVQ Max
40/100- ECI—
- Price$1.20 / $4.80
- Context131K
- Alibaba (Qwen)
Qwen3-Next 80B-A3B (Thinking)
34/100- ECI—
- Price$0.50 / $6.00
- Context131K
QVQ Max is our pick
QVQ Max is the better all-round choice, scoring 40/100 against Qwen3-Next 80B-A3B (Thinking) (34) and Apertus 70B (33). It leads on inputs & features. Apertus 70B wins 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 priceApertus 70BApertus 70B $1.22 · Qwen3-Next 80B-A3B (Thinking) $1.88 · QVQ Max $2.10 per 1M tokens (3:1 blend)
- Longest contextQVQ Max and Qwen3-Next 80B-A3B (Thinking)QVQ Max 131,072 · Qwen3-Next 80B-A3B (Thinking) 131,072 · Apertus 70B 65,536 tokens
- Widest inputsQVQ MaxApertus 70B: Text · QVQ Max: Text, Images · Qwen3-Next 80B-A3B (Thinking): Text
- Self-hostingApertus 70B and Qwen3-Next 80B-A3B (Thinking)Publishes downloadable weights (Apache-2.0)
| Measure | Weight | Apertus 70B | QVQ Max | Qwen3-Next 80B-A3B (Thinking) |
|---|---|---|---|---|
| Price | 50% | 46 | 35 | 37 |
| Inputs & features | 30% | 25 | 60 | 35 |
| Context window | 20% | 12 | 24 | 24 |
| Overall | 100% | 33/100 | 40/100 | 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 | QVQ MaxAlibaba (Qwen) | Qwen3-Next 80B-A3B (Thinking)Alibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.82 | $1.20 | $0.50 (best) |
| Output | $2.42 (best) | $4.80 | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $1.22 (best) | $2.10 | $1.88 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 65,536 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Max output | 8,192 tokens | 8,192 tokens | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | — | qvq-max | qwen3-next-80b-a3b-thinking |
| API providers | 3 | 1 | 10 (best) |
| Released | Sep 2, 2025 | Mar 25, 2025 | Sep 2025 |
| Knowledge cutoff | Sep 2025 | Apr 2024 | 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
- QVQ Max$21.60
- Qwen3-Next 80B-A3B (Thinking)$17.00
Which should you choose?
Which is better: Apertus 70B, QVQ Max or Qwen3-Next 80B-A3B (Thinking)?
QVQ Max is the better all-round choice, scoring 40/100 against Qwen3-Next 80B-A3B (Thinking) (34) and Apertus 70B (33). It leads on inputs & features. Apertus 70B wins 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, Apertus 70B, QVQ Max 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); QVQ Max costs $1.20 input / $4.80 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) and $2.10 for QVQ Max (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Apertus 70B has not been scored yet, QVQ Max 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, QVQ Max 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. All three support tool calling for agent workflows.
Which has the bigger context window?
QVQ Max and Qwen3-Next 80B-A3B (Thinking) have the largest context windows (131,072 and 131,072 tokens), against 65,536 for Apertus 70B. Maximum output per response: Apertus 70B up to 8,192, QVQ Max 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; QVQ Max accepts text and images; Qwen3-Next 80B-A3B (Thinking) accepts text. QVQ Max handles the widest range of inputs.
Are any of these open source?
Apertus 70B and Qwen3-Next 80B-A3B (Thinking) publishes its weights (Apache-2.0) and can be self-hosted; QVQ Max is proprietary.
Which is newer?
Apertus 70B is the newest, released Sep 2, 2025. Qwen3-Next 80B-A3B (Thinking) came out Sep 2025; QVQ Max came out Mar 25, 2025. Knowledge cutoff: Apertus 70B Sep 2025, QVQ Max Apr 2024, 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.
