QVQ Max vs GPT OSS 120B
GPT OSS 120B comes out ahead, 57 to 40 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)
QVQ Max
40/100- ECI—
- Price$1.20 / $4.80
- Context131K
- Our pick
OpenAI
GPT OSS 120B
57/100- ECI140.0
- Price$0.15 / $0.60
- Context131K
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Make it a three-way comparison.
GPT OSS 120B is our pick
GPT OSS 120B is the better all-round choice, scoring 57/100 against QVQ Max (40). It leads on price. QVQ Max wins on inputs & features. 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 priceGPT OSS 120BGPT OSS 120B $0.263 · QVQ Max $2.10 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQVQ Max 131,072 · GPT OSS 120B 131,072 tokens
- Widest inputsQVQ MaxQVQ Max: Text, Images · GPT OSS 120B: Text
- Self-hostingGPT OSS 120BPublishes downloadable weights
| Measure | Weight | QVQ Max | GPT OSS 120B |
|---|---|---|---|
| Price | 50% | 35 | 77 |
| Inputs & features | 30% | 60 | 45 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 40/100 | 57/100 |
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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 140.0 |
| ECI rank | — | #99 of 148 |
| GPQA DiamondGraduate-level science questions | — | 75.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 88.9% |
| Price per million tokens | ||
| Input | $1.20 | $0.15 (best) |
| Output | $4.80 | $0.60 (best) |
| Cached input | — | — |
| Blended (3:1) | $2.10 | $0.263 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 36 providers |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 32,768 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | qvq-max | — |
| API providers | 1 | 39 (best) |
| Released | Mar 25, 2025 | Aug 5, 2025 |
| Knowledge cutoff | Apr 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
QVQ Max$21.60
GPT OSS 120B$2.70
Which should you choose?
Which is better: QVQ Max or GPT OSS 120B?
GPT OSS 120B is the better all-round choice, scoring 57/100 against QVQ Max (40). It leads on price. QVQ Max wins on inputs & features. 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, QVQ Max or GPT OSS 120B?
GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 36 API providers). 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 $0.263 per million tokens for GPT OSS 120B versus $2.10 for QVQ Max (8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. QVQ Max has not been scored yet and GPT OSS 120B has an ECI of 140.0.
Which is better for coding?
There are no published SWE-bench Verified results for QVQ Max and GPT OSS 120B 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?
QVQ Max and GPT OSS 120B share the same 131,072-token context window. Maximum output per response: QVQ Max up to 8,192, GPT OSS 120B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
QVQ Max accepts text and images; GPT OSS 120B accepts text. QVQ Max handles the widest range of inputs.
Are any of these open source?
GPT OSS 120B publishes its weights and can be self-hosted; QVQ Max is proprietary.
Which is newer?
GPT OSS 120B is the newest, released Aug 5, 2025. QVQ Max came out Mar 25, 2025. Knowledge cutoff: QVQ Max Apr 2024.
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.