Grok 4.3 vs Mistral Medium 3.5

Choose Grok 4.3 if you want…

• ✓Higher intelligence (Artificial Analysis index 38)
• ✓Lower price ($1.56 / 1M blended)
• ✓Larger context window (1M)

Choose Mistral Medium 3.5 if you want…

• ✓Faster output (~132.8 tokens/sec)

Grok 4.3

Grok 4.3 made a deliberate trade: xAI stopped chasing frontier performance and built something more practical instead. The result is a model that earns its keep through native X/Twitter integration — pulling posts seconds old when news breaks — and a 1 million token context window that handles entire codebases or lengthy regulatory documents in a single pass. At $1.25 per million input tokens, it arrives 40-60% cheaper than its predecessor Grok-4, and users find real value in its DeepSearch mode, which combines live web data with X discussions in a way that rivals Perplexity for current-events research. Frontend developers report genuinely polished web UI output, moving past the "cheap AI demo" look. The honest trade-off: creative writers consistently find it too literal and verbose, and its 16-second time-to-first-token sits at the high end for reasoning models in this price range. If your work is anchored in real-time information or long-document analysis rather than narrative craft, Grok 4.3 offers a focused, cost-sensible tool.

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.