Inkling Small vs Mistral Large 3 vs Mistral Large 4
Too close to call on our weighted score (Inkling Small 59, Mistral Large 4 56, Mistral Large 3 52). The right pick depends on what you value most.
Thinking MachinesInkling Small
59/100- ECI150.5
- Price$0.58 / $1.44
- Context1.05M
Mistral AIMistral Large 3
52/100- ECI—
- Price$0.50 / $1.50
- Context262K
- Mistral AI
Mistral Large 4
56/100- ECI150.6
- Price$0.70 / $2.10
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 3 points (Inkling Small 59/100, Mistral Large 4 56/100, Mistral Large 3 52/100), so choose by what matters most for your work: Mistral Large 3 on price. 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 priceMistral Large 3Mistral Large 3 $0.75 · Inkling Small $0.795 · Mistral Large 4 $1.05 per 1M tokens (3:1 blend)
- Longest contextInkling Small and Mistral Large 4Inkling Small 1,048,576 · Mistral Large 4 1,048,576 · Mistral Large 3 262,144 tokens
- Widest inputsInkling SmallInkling Small: Text, Images, Audio · Mistral Large 3: Text, Images · Mistral Large 4: Text, Images
- Self-hostingInkling Small and Mistral Large 3Publishes downloadable weights (Apache-2.0)
| Measure | Weight | Inkling Small | Mistral Large 3 | Mistral Large 4 |
|---|---|---|---|---|
| Price | 50% | 52 | 53 | 47 |
| Inputs & features | 30% | 70 | 60 | 70 |
| Context window | 20% | 61 | 37 | 61 |
| Overall | 100% | 59/100 | 52/100 | 56/100 |
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 | Inkling SmallThinking Machines | Mistral Large 3Mistral AI | Mistral Large 4Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.5 | — | 150.6 (best) |
| ECI rank | #58 of 165 | — | #57 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 88.5% (best) | — | 88.1% |
| FrontierMath Tiers 1–3Research-level mathematics | 46.3% | — | 58.6% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 90.0% | — | 98.3% (best) |
| SimpleQA VerifiedShort factual questions | 19.1% | — | 20.0% (best) |
| Price per million tokens | |||
| Input | $0.58 | $0.50 (best) | $0.70 |
| Output | $1.44 (best) | $1.50 | $2.10 |
| Cached input | $0.116 | $0.05 (best) | $0.07 |
| Blended (3:1) | $0.795 | $0.75 (best) | $1.05 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Thinking Machines API | Official Mistral API | Official Mistral API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 1,048,576 tokens (best) | 262,144 tokens | 262,144 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | No | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | thinkingmachines/Inkling-Small | mistral-large-2512 | mistral-large-4 |
| API providers | 12 | 17 (best) | 15 |
| Released | Jul 30, 2026 | Dec 2, 2025 | Oct 6, 2026 |
| Knowledge cutoff | — | Nov 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Inkling Small$8.68
- Mistral Large 3$8.00
- Mistral Large 4$11.20
Which should you choose?
Which is better: Inkling Small, Mistral Large 3 or Mistral Large 4?
It is close. Our weighted score puts them within 3 points (Inkling Small 59/100, Mistral Large 4 56/100, Mistral Large 3 52/100), so choose by what matters most for your work: Mistral Large 3 on price. 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, Inkling Small, Mistral Large 3 or Mistral Large 4?
Mistral Large 3 is cheaper at $0.50 input / $1.50 output per million tokens (official Mistral API price). Inkling Small costs $0.58 input / $1.44 output per million tokens (official Thinking Machines API price); Mistral Large 4 costs $0.70 input / $2.10 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.75 per million tokens for Mistral Large 3 versus $0.795 for Inkling Small (1.1× as much) and $1.05 for Mistral Large 4 (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Inkling Small has an ECI of 150.5, Mistral Large 3 has not been scored yet and Mistral Large 4 has an ECI of 150.6.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling Small, Mistral Large 3 and Mistral Large 4 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?
Inkling Small and Mistral Large 4 have the largest context windows (1,048,576 and 1,048,576 tokens), against 262,144 for Mistral Large 3. Maximum output per response: Inkling Small up to 1,048,576, Mistral Large 3 up to 262,144, Mistral Large 4 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Inkling Small accepts text, images and audio; Mistral Large 3 accepts text and images; Mistral Large 4 accepts text and images. Inkling Small handles the widest range of inputs.
Are any of these open source?
Inkling Small and Mistral Large 3 publishes its weights (Apache-2.0) and can be self-hosted; Mistral Large 4 is proprietary.
Which is newer?
Mistral Large 4 is the newest, released Oct 6, 2026. Inkling Small came out Jul 30, 2026; Mistral Large 3 came out Dec 2, 2025. Knowledge cutoff: Mistral Large 3 Nov 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.
