Model comparison
Compare Inkling and Mistral Medium 3.5 using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| InklingThinking Machines Lab | Thinking Machines Lab | No reviewed rate |
| Mistral Medium 3.5Mistral AI | Mistral AI | No reviewed rate |
Quick take
Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows.
A 975B model is a serious serving project even with sparse activation. Compare the exact hosted or self-hosted route, and do not assume the model's 1M maximum context is available on every provider.
Mistral's open-weight frontier model for demanding multimodal, coding, reasoning, and agent workflows, with a 256K context window.
The headline token price applies to Mistral's standard hosted endpoint. Regional inference costs more, and self-hosting shifts the bill to GPUs, operations, and support.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | Inkling | Mistral Medium 3.5 |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | Up to 1M tokens; Tinker offers 64K and 256K | 256K tokens combined |
| Maximum outputProvider-published response limit, where available. | Not separately published | Not separately published |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | Not published | Not published |
| Input priceCurrent standard list price per million input tokens unless noted. | Hosting dependent | $1.50 / 1M |
| Output priceCurrent standard list price per million output tokens unless noted. | Hosting dependent | $7.50 / 1M |
| InputsMedia types accepted by the listed model endpoint. | Text, image, audio | Text, image |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Agentic coding, tools, Python-assisted vision, controllable thinking | Functions, agents, built-in tools, structured and predicted outputs |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
The open weights can be self-hosted so request data stays in infrastructure you control. Tinker and partner-hosted routes have separate retention and training-use terms that must be checked with the selected provider.
Mistral's commercial terms exclude model training by default except when a customer opts in or uses designated Labs or preview models. Standard API input and output retention is generally 30 rolling days for abuse monitoring unless zero data retention is enabled.
Provider and API links
Frequently asked questions
Inkling: Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows. Mistral Medium 3.5: Mistral's open-weight frontier model for demanding multimodal, coding, reasoning, and agent workflows, with a 256K context window.
Consider Inkling when your priority is Teams that want an adaptable open-weight foundation model. Consider Mistral Medium 3.5 when your priority is Complex coding and agent workflows. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
