Head to head
GLM 5.1 vs Mistral Large 3
GLM 5.1 (Zhipu AI) and Mistral Large 3 (Mistral) compared on intelligence, speed, context, and price — and which to choose. Both run on just4o.chat from one chat.
| Metric | GLM 5.1 | Mistral Large 3 |
|---|---|---|
| Intelligence (AA index) | 40 ✓ | 16 |
| Output speed (tokens/sec) | 83.5 ✓ | 49.1 |
| Context window | 200K | 256K ✓ |
| Max output | 128K | — |
| Input price / 1M | $1.4 | $0.5 ✓ |
| Output price / 1M | $4.4 | $1.5 ✓ |
| Released | 2026-03 | 2025-12 |
Choose GLM 5.1 if you want…
- Higher intelligence (Artificial Analysis index 40)
- Faster output (~83.5 tokens/sec)
Choose Mistral Large 3 if you want…
- Lower price ($0.75 / 1M blended)
- Larger context window (256K)
GLM 5.1
GLM-5.1 from Z.ai is built for one thing above all else: software engineering that runs on its own. A 754-billion parameter Mixture-of-Experts model, it tops the SWE-Bench Pro leaderboard at 58.4%, edging out both GPT-5.4 and Claude Opus 4.6 on real-world coding tasks. What sets it apart in practice is stamina — it can pursue a single engineering goal autonomously for up to eight hours, sustaining hundreds of iterations and thousands of tool calls without human intervention. Users consistently praise this long-horizon execution for agent-based workflows where other models stall. It also delivers fast responses, with a time-to-first-token of 1.33 seconds against a class median of 2.37 seconds. The honest trade-off: GLM-5.1 accepts text only, with no image input, making it a poor fit for visual debugging or UI-centric tasks. It also tends toward verbosity in practice, which can inflate token costs. For teams building autonomous coding pipelines, though, it earns its place at the top of the leaderboard.
Full GLM 5.1 details →Mistral Large 3
Mistral Large 3 is the French lab's flagship dense model, and on just4o.chat it runs through the Vercel AI Gateway under the mistral/mistral-large-3 route. It pairs strong general reasoning with the multilingual fluency Mistral is known for — European languages in particular — and reliable function calling for tool-driven workflows. A 256k-token context window is roomy enough for long documents, multi-file code, or extended chats without truncation, and at $0.50 per million input and $1.50 per million output tokens it sits at the affordable end of frontier-class models. On just4o.chat it is a base-tier model available on every plan, billed at 2 base requests per send before length multipliers. One practical note worth flagging up front: like the rest of the Mistral lineup here, it has no native web search, and it is text-only — no image input. For teams that want a capable, cost-disciplined generalist with first-rate multilingual handling, it is an easy default.
Full Mistral Large 3 details →FAQ
Which is better, GLM 5.1 or Mistral Large 3?
GLM 5.1 leads on 2 of the headline metrics (higher intelligence (artificial analysis index 40); faster output (~83.5 tokens/sec)), while Mistral Large 3 wins on lower price ($0.75 / 1m blended); larger context window (256k). The right pick depends on whether you prioritise capability, speed, or cost.
Is GLM 5.1 or Mistral Large 3 cheaper?
Mistral Large 3 is cheaper at $0.75 per 1M tokens (blended), versus $2.15.
Can I use both GLM 5.1 and Mistral Large 3?
Yes. Both are available on just4o.chat from a single chat — you can switch between them per message with no separate subscriptions.