Gemini 2.5 Pro vs o4-mini vs solar-mini
Too close to call on our weighted score (Gemini 2.5 Pro 54, solar-mini 52, o4-mini 46). The right pick depends on what you value most.
GoogleGemini 2.5 Pro
54/100- ECI145.3
- Price$1.25 / $10.00
- Context1.05M
OpenAIo4-mini
46/100- ECI145.6
- Price$1.10 / $4.40
- Context200K
Upstage
solar-mini
52/100- ECI—
- Price$0.15 / $0.15
- Context33K
Too close to call
It is close. Our weighted score puts them within 2 points (Gemini 2.5 Pro 54/100, solar-mini 52/100, o4-mini 46/100), so choose by what matters most for your work: solar-mini on price and Gemini 2.5 Pro for long inputs. 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 pricesolar-minisolar-mini $0.15 · o4-mini $1.93 · Gemini 2.5 Pro $3.44 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · o4-mini 200,000 · solar-mini 32,768 tokens
- Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · o4-mini: Text, Images · solar-mini: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 2.5 Pro | o4-mini | solar-mini |
|---|---|---|---|---|
| Price | 50% | 24 | 36 | 89 |
| Inputs & features | 30% | 100 | 70 | 25 |
| Context window | 20% | 61 | 32 | 0 |
| Overall | 100% | 54/100 | 46/100 | 52/100 |
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 | Gemini 2.5 ProGoogle | o4-miniOpenAI | solar-miniUpstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.3 | 145.6 (best) | — |
| ECI rank | #78 of 148 | #76 of 148 (best) | — |
| GPQA DiamondGraduate-level science questions | 85.3% (best) | 79.6% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 24.6% | 36.1% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.7% (best) | 81.7% | — |
| SWE-bench VerifiedFixing real GitHub issues | 57.6% | — | — |
| SimpleQA VerifiedShort factual questions | — | 19.6% | — |
| Price per million tokens | |||
| Input | $1.25 | $1.10 | $0.15 (best) |
| Output | $10.00 | $4.40 | $0.15 (best) |
| Cached input | $0.125 (best) | $0.275 | — |
| Blended (3:1) | $3.44 | $1.93 | $0.15 (best) |
| Long-context rate | Over 200K: $2.50 / $15.00 | Same rate | Same rate |
| Price source | Official Google API | Official OpenAI API | Official Upstage API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 200,000 tokens | 32,768 tokens |
| Max output | 65,536 tokens | 100,000 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gemini-2.5-pro | o4-mini | solar-mini |
| API providers | 22 (best) | 19 | 1 |
| Released | Jun 17, 2025 | Apr 16, 2025 | Jun 12, 2024 |
| Knowledge cutoff | Jan 2025 | May 2024 | Sep 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.5 Pro$32.50
- o4-mini$19.80
- solar-mini$1.80
Which should you choose?
Which is better: Gemini 2.5 Pro, o4-mini or solar-mini?
It is close. Our weighted score puts them within 2 points (Gemini 2.5 Pro 54/100, solar-mini 52/100, o4-mini 46/100), so choose by what matters most for your work: solar-mini on price and Gemini 2.5 Pro for long inputs. 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, Gemini 2.5 Pro, o4-mini or solar-mini?
solar-mini is cheaper at $0.15 input / $0.15 output per million tokens (official Upstage API price). o4-mini costs $1.10 input / $4.40 output per million tokens (official OpenAI API price); Gemini 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for solar-mini versus $1.93 for o4-mini (13× as much) and $3.44 for Gemini 2.5 Pro (23× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Pro has an ECI of 145.3, o4-mini has an ECI of 145.6 and solar-mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o4-mini and solar-mini 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?
Gemini 2.5 Pro has the largest context window at 1,048,576 tokens, against 200,000 for o4-mini and 32,768 for solar-mini. Maximum output per response: Gemini 2.5 Pro up to 65,536, o4-mini up to 100,000, solar-mini up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Pro accepts text, images, PDFs, audio and video; o4-mini accepts text and images; solar-mini accepts text. Gemini 2.5 Pro handles the widest range of inputs.
Are any of these open source?
No. Gemini 2.5 Pro, o4-mini and solar-mini are proprietary and only available through APIs and apps.
Which is newer?
Gemini 2.5 Pro is the newest, released Jun 17, 2025. o4-mini came out Apr 16, 2025; solar-mini came out Jun 12, 2024. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, o4-mini May 2024, solar-mini Sep 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.
