Gemma 4 26B A4B IT vs GPT OSS 120B vs Qwen3.5 Flash
Qwen3.5 Flash comes out ahead, 73 to 68 and 58 on our weighted score, and it is the cheaper option too.
Google
Gemma 4 26B A4B IT
68/100- ECI142.0
- Price$0.112 / $0.40
- Context262K
OpenAI
GPT OSS 120B
58/100- ECI139.8
- Price$0.15 / $0.60
- Context131K
- Our pick
Alibaba (Qwen)
Qwen3.5 Flash
73/100- ECI143.6
- Price$0.10 / $0.40
- Context1M
Qwen3.5 Flash is our pick
Qwen3.5 Flash is the better all-round choice, scoring 73/100 against Gemma 4 26B A4B IT (68) and GPT OSS 120B (58). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 FlashCapabilities Index (ECI): Qwen3.5 Flash 143.6 · Gemma 4 26B A4B IT 142.0 · GPT OSS 120B 139.8
- Lowest priceQwen3.5 FlashQwen3.5 Flash $0.175 · Gemma 4 26B A4B IT $0.184 · GPT OSS 120B $0.263 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · Gemma 4 26B A4B IT 262,144 · GPT OSS 120B 131,072 tokens
- Widest inputsQwen3.5 FlashGemma 4 26B A4B IT: Text, Images · GPT OSS 120B: Text · Qwen3.5 Flash: Text, Images, Video
- Self-hostingGemma 4 26B A4B IT and GPT OSS 120BPublishes downloadable weights
| Measure | Weight | Gemma 4 26B A4B IT | GPT OSS 120B | Qwen3.5 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 67 | 64 | 69 |
| Price | 25% | 81 | 74 | 82 |
| Inputs & features | 15% | 70 | 35 | 80 |
| Context window | 10% | 37 | 25 | 60 |
| Overall | 100% | 68/100 | 58/100 | 73/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 142.0 | 139.8 | 143.6 (best) |
| ECI rank | #103 of 165 | #114 of 165 | #95 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 73.2% | 75.8% | 82.3% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 18.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 82.2% | 88.9% (best) | 84.4% |
| SimpleQA VerifiedShort factual questions | — | — | 20.3% |
| Price per million tokens | |||
| Input | $0.112 | $0.15 | $0.10 (best) |
| Output | $0.40 (best) | $0.60 | $0.40 (best) |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.184 | $0.263 | $0.175 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 26 providers | Median of 65 providers | Official Alibaba API |
| Limits | |||
| Context window | 262,144 tokens | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens | 32,768 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | gemma-4-26b-a4b-it | — | qwen3.5-flash |
| API providers | 29 | 67 (best) | 9 |
| Released | Apr 2, 2026 | Aug 5, 2025 | Feb 23, 2026 |
| Knowledge cutoff | — | Jun 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Gemma 4 26B A4B IT$1.92
GPT OSS 120B$2.70
Qwen3.5 Flash$1.80
Which should you choose?
Which is better: Gemma 4 26B A4B IT, GPT OSS 120B or Qwen3.5 Flash?
Qwen3.5 Flash is the better all-round choice, scoring 73/100 against Gemma 4 26B A4B IT (68) and GPT OSS 120B (58). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemma 4 26B A4B IT, GPT OSS 120B or Qwen3.5 Flash?
Qwen3.5 Flash is cheaper at $0.10 input / $0.40 output per million tokens (official Alibaba API price). Gemma 4 26B A4B IT costs $0.112 input / $0.40 output per million tokens (median across 26 API providers); GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 65 API providers). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Qwen3.5 Flash versus $0.184 for Gemma 4 26B A4B IT (1× as much) and $0.263 for GPT OSS 120B (1.5× as much).
Which scores higher on benchmarks?
Qwen3.5 Flash scores higher on the Capabilities Index (ECI): Qwen3.5 Flash 143.6 (#95 of 165), Gemma 4 26B A4B IT 142.0 (#103 of 165) and GPT OSS 120B 139.8 (#114 of 165). The confidence ranges of the top two overlap (141.4–145.0 vs 139.0–143.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 Flash 82.3%, GPT OSS 120B 75.8%, Gemma 4 26B A4B IT 73.2%; OTIS Mock AIME 2024–2025 — GPT OSS 120B 88.9%, Qwen3.5 Flash 84.4%, Gemma 4 26B A4B IT 82.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 4 26B A4B IT, GPT OSS 120B and Qwen3.5 Flash yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 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?
Qwen3.5 Flash has the largest context window at 1,000,000 tokens, against 262,144 for Gemma 4 26B A4B IT and 131,072 for GPT OSS 120B. Maximum output per response: Gemma 4 26B A4B IT up to 32,768, GPT OSS 120B up to 32,768, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemma 4 26B A4B IT accepts text and images; GPT OSS 120B accepts text; Qwen3.5 Flash accepts text, images and video. Qwen3.5 Flash handles the widest range of inputs.
Are any of these open source?
Gemma 4 26B A4B IT and GPT OSS 120B publishes its weights and can be self-hosted; Qwen3.5 Flash is proprietary.
Which is newer?
Gemma 4 26B A4B IT is the newest, released Apr 2, 2026. Qwen3.5 Flash came out Feb 23, 2026; GPT OSS 120B came out Aug 5, 2025. Knowledge cutoff: GPT OSS 120B Jun 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 Nov 2, 2026.