o4-mini-deep-research vs solar-mini vs Codestral
o4-mini-deep-research comes out ahead, 49 to 29 and 15 on our weighted score.
- Our pick
OpenAI
o4-mini-deep-research
49/100- ECI—
- Price—
- Context200K
Upstage
solar-mini
15/100- ECI—
- Price$0.15 / $0.15
- Context33K
Mistral AI
Codestral
29/100- ECI—
- Price$0.30 / $0.90
- Context256K
o4-mini-deep-research is our pick
o4-mini-deep-research is the better all-round choice, scoring 49/100 against Codestral (29) and solar-mini (15). It leads on inputs & features. Codestral wins on context window. The score weighs inputs & features 60%, context window 40%. 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 · Codestral $0.45 per 1M tokens (3:1 blend) · o4-mini-deep-research unpriced
- Longest contextCodestralCodestral 256,000 · o4-mini-deep-research 200,000 · solar-mini 32,768 tokens
- Widest inputso4-mini-deep-researcho4-mini-deep-research: Text, Images · solar-mini: Text · Codestral: Text
- Self-hostingCodestralPublishes downloadable weights
| Measure | Weight | o4-mini-deep-research | solar-mini | Codestral |
|---|---|---|---|---|
| Inputs & features | 60% | 60 | 25 | 25 |
| Context window | 40% | 32 | 0 | 36 |
| Overall | 100% | 49/100 | 15/100 | 29/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | solar-miniUpstage | ||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.15 (best) | $0.30 |
| Output | — | $0.15 (best) | $0.90 |
| Cached input | — | — | $0.03 |
| Blended (3:1) | — | $0.15 (best) | $0.45 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Upstage API | Official Mistral API |
| Limits | |||
| Context window | 200,000 tokens | 32,768 tokens | 256,000 tokens (best) |
| Max output | 100,000 tokens (best) | 4,096 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | solar-mini | codestral-latest |
| API providers | — | 1 | 3 (best) |
| Released | Jun 26, 2024 | Jun 12, 2024 | May 29, 2024 |
| Knowledge cutoff | May 2024 | Sep 2024 | Oct 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
o4-mini-deep-research—
- solar-mini$1.80
Codestral$4.80
Which should you choose?
Which is better: o4-mini-deep-research, solar-mini or Codestral?
o4-mini-deep-research is the better all-round choice, scoring 49/100 against Codestral (29) and solar-mini (15). It leads on inputs & features. Codestral wins on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, o4-mini-deep-research, solar-mini or Codestral?
solar-mini is cheaper at $0.15 input / $0.15 output per million tokens (official Upstage API price). Codestral costs $0.30 input / $0.90 output per million tokens (official Mistral 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 $0.45 for Codestral (3× as much). o4-mini-deep-research has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. o4-mini-deep-research has not been scored yet, solar-mini has not been scored yet and Codestral has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o4-mini-deep-research, solar-mini and Codestral 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?
Codestral has the largest context window at 256,000 tokens, against 200,000 for o4-mini-deep-research and 32,768 for solar-mini. Maximum output per response: o4-mini-deep-research up to 100,000, solar-mini up to 4,096, Codestral up to 4,096 tokens.
Which can read images, PDFs, audio or video?
o4-mini-deep-research accepts text and images; solar-mini accepts text; Codestral accepts text. o4-mini-deep-research handles the widest range of inputs.
Are any of these open source?
Codestral publishes its weights and can be self-hosted; o4-mini-deep-research and solar-mini is proprietary.
Which is newer?
o4-mini-deep-research is the newest, released Jun 26, 2024. solar-mini came out Jun 12, 2024; Codestral came out May 29, 2024. Knowledge cutoff: o4-mini-deep-research May 2024, solar-mini Sep 2024, Codestral Oct 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.