Inkling vs Mistral Medium 3.5

Choose Inkling if you want…

• ✓Higher intelligence (Artificial Analysis index 46)
• ✓Lower price ($1.76 / 1M blended)

Choose Mistral Medium 3.5 if you want…

• ✓A comparable all-rounder — they trade blows on the headline metrics.

Inkling

Inkling is Thinking Machines Lab's first open-weights model, and on just4o.chat it runs through the Vercel AI Gateway under thinkingmachines/inkling. It is a multimodal MoE with 975B total parameters and 41B active, trained to reason over text, images, and audio in a shared space rather than bolting on separate encoders. Controllable thinking effort lets you trade latency for depth, function calling supports agentic workflows, and a 256k context window on the gateway is roomy enough for long multimodal sessions. It is a base-tier model on just4o.chat, billed at 4 base requests per send before length multipliers, at $1.00 per million input and $4.05 per million output tokens (cached input $0.17). Practical caveats: no native web search on this route, and chat attachments currently emphasize image input even though the model itself understands audio. For teams that want an open, customizable multimodal foundation with ZDR-compatible gateway routing, Inkling is a strong addition.

Mistral Medium 3.5

Mistral Medium 3.5 is Mistral's multimodal flagship on just4o.chat, served through the Vercel AI Gateway as mistral/mistral-medium-3.5. It combines frontier text reasoning with native image understanding in a single model, so you can hand it a screenshot, chart, or document image alongside your prompt and get a grounded answer back. A 256k-token context window handles long inputs comfortably, and function calling makes it suitable for agentic and tool-driven work. It is a Premium model on just4o.chat, billed at 3 premium requests per send before length multipliers, reflecting its higher provider output price of $7.50 per million tokens ($1.50 per million input). The honest trade-offs: no native web search, and as a vision-capable generalist rather than a dedicated reasoning model, it does not expose a step-by-step thinking budget the way Magistral does. For multimodal analysis, visual document work, and high-quality general assistance where image input matters, it is the model to reach for.