Gemma 3 12B IT vs o3-deep-research vs Qwen2.5 7B Instruct
Gemma 3 12B IT comes out ahead, 69 to 62 and 24 on our weighted score, though Qwen2.5 7B Instruct is 17% cheaper per token.
- Our pick
GoogleGemma 3 12B IT
69/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
OpenAIo3-deep-research
24/100- ECI—
- Price$9.00 / $36.00
- Context200K
Alibaba (Qwen)Qwen2.5 7B Instruct
62/100- ECI118.5
- Price$0.05 / $0.10
- Context131K
Gemma 3 12B IT is our pick
Gemma 3 12B IT is the better all-round choice, scoring 69/100 against Qwen2.5 7B Instruct (62) and o3-deep-research (24). o3-deep-research wins on inputs & features and context window. 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 priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Gemma 3 12B IT $0.075 · o3-deep-research $15.75 per 1M tokens (3:1 blend)
- Longest contexto3-deep-researcho3-deep-research 200,000 · Gemma 3 12B IT 131,072 · Qwen2.5 7B Instruct 131,072 tokens
- Widest inputsGemma 3 12B IT and o3-deep-researchGemma 3 12B IT: Text, Images · o3-deep-research: Text, Images · Qwen2.5 7B Instruct: Text
- Self-hostingGemma 3 12B IT and Qwen2.5 7B InstructPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Gemma 3 12B IT | o3-deep-research | Qwen2.5 7B Instruct |
|---|---|---|---|---|
| Price | 50% | 99 | 0 | 100 |
| Inputs & features | 30% | 50 | 60 | 25 |
| Context window | 20% | 25 | 32 | 25 |
| Overall | 100% | 69/100 | 24/100 | 62/100 |
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 | Gemma 3 12B ITGoogle | o3-deep-researchOpenAI | Qwen2.5 7B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 123.5 (best) | — | 118.5 |
| ECI rank | #151 of 165 (best) | — | #159 of 165 |
| GPQA DiamondGraduate-level science questions | 39.5% (best) | — | 35.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 16.7% (best) | — | 2.5% |
| Price per million tokens | |||
| Input | $0.05 (best) | $9.00 | $0.05 (best) |
| Output | $0.15 | $36.00 | $0.10 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.075 | $15.75 | $0.063 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 12 providers | Median of 1 providers | Median of 3 providers |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 131,072 tokens |
| Max output | 131,072 tokens (best) | 100,000 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache 2.0 |
| API model ID | — | — | — |
| API providers | 13 (best) | 1 | 4 |
| Released | Mar 12, 2025 | Jun 26, 2025 | Sep 19, 2024 |
| Knowledge cutoff | Aug 2024 | May 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 3 12B IT$0.80
- o3-deep-research$162.00
- Qwen2.5 7B Instruct$0.70
Which should you choose?
Which is better: Gemma 3 12B IT, o3-deep-research or Qwen2.5 7B Instruct?
Gemma 3 12B IT is the better all-round choice, scoring 69/100 against Qwen2.5 7B Instruct (62) and o3-deep-research (24). o3-deep-research wins on inputs & features and context window. 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, Gemma 3 12B IT, o3-deep-research or Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is cheaper at $0.05 input / $0.10 output per million tokens (median across 3 API providers). Gemma 3 12B IT costs $0.05 input / $0.15 output per million tokens (median across 12 API providers); o3-deep-research costs $9.00 input / $36.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Qwen2.5 7B Instruct versus $0.075 for Gemma 3 12B IT (1.2× as much) and $15.75 for o3-deep-research (252× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 3 12B IT has an ECI of 123.5, o3-deep-research has not been scored yet and Qwen2.5 7B Instruct has an ECI of 118.5.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3 12B IT, o3-deep-research and Qwen2.5 7B Instruct 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?
o3-deep-research has the largest context window at 200,000 tokens, against 131,072 for Gemma 3 12B IT and 131,072 for Qwen2.5 7B Instruct. Maximum output per response: Gemma 3 12B IT up to 131,072, o3-deep-research up to 100,000, Qwen2.5 7B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 12B IT accepts text and images; o3-deep-research accepts text and images; Qwen2.5 7B Instruct accepts text. Gemma 3 12B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3 12B IT and Qwen2.5 7B Instruct publishes its weights (Apache 2.0) and can be self-hosted; o3-deep-research is proprietary.
Which is newer?
o3-deep-research is the newest, released Jun 26, 2025. Gemma 3 12B IT came out Mar 12, 2025; Qwen2.5 7B Instruct came out Sep 19, 2024. Knowledge cutoff: Gemma 3 12B IT Aug 2024, o3-deep-research May 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.
