Qwen3 235B-A22B Instruct 2507 vs Gemini 2.5 Flash vs GPT OSS 120B
Gemini 2.5 Flash comes out ahead, 68 to 61 and 58 on our weighted score, though GPT OSS 120B is 3.2× cheaper per token.
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
58/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
- Our pick
GoogleGemini 2.5 Flash
68/100- ECI140.8
- Price$0.30 / $2.50
- Context1.05M
OpenAIGPT OSS 120B
61/100- ECI140.0
- Price$0.15 / $0.60
- Context131K
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GPT OSS 120B (61) and Qwen3 235B-A22B Instruct 2507 (58). It leads on inputs & features and context window. GPT OSS 120B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 2.5 FlashCapabilities Index (ECI): Gemini 2.5 Flash 140.8 · GPT OSS 120B 140.0 · Qwen3 235B-A22B Instruct 2507 138.9
- Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.30 · Gemini 2.5 Flash $0.85 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · Qwen3 235B-A22B Instruct 2507 262,144 · GPT OSS 120B 131,072 tokens
- Widest inputsGemini 2.5 FlashQwen3 235B-A22B Instruct 2507: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GPT OSS 120B: Text
- Self-hostingQwen3 235B-A22B Instruct 2507 and GPT OSS 120BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Qwen3 235B-A22B Instruct 2507 | Gemini 2.5 Flash | GPT OSS 120B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 67 | 65 |
| Price | 25% | 75 | 53 | 77 |
| Inputs & features | 15% | 25 | 100 | 45 |
| Context window | 10% | 37 | 61 | 24 |
| Overall | 100% | 58/100 | 68/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) | Gemini 2.5 FlashGoogle | GPT OSS 120BOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.9 | 140.8 (best) | 140.0 |
| ECI rank | #105 of 148 | #97 of 148 (best) | #99 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 75.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 88.9% |
| Price per million tokens | |||
| Input | $0.15 (best) | $0.30 | $0.15 (best) |
| Output | $0.75 | $2.50 | $0.60 (best) |
| Cached input | — | $0.03 | — |
| Blended (3:1) | $0.30 | $0.85 | $0.263 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Official Google API | Median of 36 providers |
| Limits | |||
| Context window | 262,144 tokens | 1,048,576 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens | 65,536 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache 2.0 | Proprietary | Open |
| API model ID | — | gemini-2.5-flash | — |
| API providers | 11 | 22 | 39 (best) |
| Released | Jul 21, 2025 | Jun 17, 2025 | Aug 5, 2025 |
| Knowledge cutoff | — | 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.
- Qwen3 235B-A22B Instruct 2507$3.00
- Gemini 2.5 Flash$8.00
- GPT OSS 120B$2.70
Which should you choose?
Which is better: Qwen3 235B-A22B Instruct 2507, Gemini 2.5 Flash or GPT OSS 120B?
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GPT OSS 120B (61) and Qwen3 235B-A22B Instruct 2507 (58). It leads on inputs & features and context window. GPT OSS 120B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B Instruct 2507, Gemini 2.5 Flash or GPT OSS 120B?
GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 36 API providers). Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers); Gemini 2.5 Flash costs $0.30 input / $2.50 output per million tokens (official Google 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 $0.30 for Qwen3 235B-A22B Instruct 2507 (1.1× as much) and $0.85 for Gemini 2.5 Flash (3.2× as much).
Which scores higher on benchmarks?
Gemini 2.5 Flash scores higher on the Capabilities Index (ECI): Gemini 2.5 Flash 140.8 (#97 of 148), GPT OSS 120B 140.0 (#99 of 148) and Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148). The confidence ranges of the top two overlap (138.5–142.3 vs 135.3–142.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B Instruct 2507, Gemini 2.5 Flash and GPT OSS 120B yet, so there is no like-for-like coding score. On overall capability, Gemini 2.5 Flash leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Flash has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3 235B-A22B Instruct 2507 and 131,072 for GPT OSS 120B. Maximum output per response: Qwen3 235B-A22B Instruct 2507 up to 16,384, Gemini 2.5 Flash up to 65,536, GPT OSS 120B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Instruct 2507 accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GPT OSS 120B accepts text. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
Qwen3 235B-A22B Instruct 2507 and GPT OSS 120B publishes its weights (Apache 2.0) and can be self-hosted; Gemini 2.5 Flash is proprietary.
Which is newer?
GPT OSS 120B is the newest, released Aug 5, 2025. Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash 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.
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