MON, NOVEMBER 09, 2026
Independent · In‑Depth · Practitioner‑Tested
LLMs

Mistral Large 4 vs GLM-5.3: Same Score, Half the Tokens

Both score 48% on the Coding Agent Index. One of them gets there on 47% fewer tokens.

🕐 7 min read 👁 14 views 📅 Nov 9, 2026
The short answer
● Same score — both 48% on the AA Coding Agent Index
● The difference — Mistral uses 47% fewer tokens per task
● Terminal-Bench 4.0 — Mistral Large 4 at 41%
● Licences — both open weight, both with conditions
● Pick by — whether you pay per token or per GPU hour

Artificial Analysis puts Mistral Large 4 and GLM-5.3 at the same score on its Coding Agent Index. That makes the tiebreak unusually clean: one of them gets there on far fewer tokens.

Mistral Large 4 GLM-5.3
AA Coding Agent Index 48% 48%
Tokens per task 47% fewer Baseline
Terminal-Bench 4.0 41% Not stated here
Parameters 1T total, around 50B active 320B/18B on the Flash variant
Weights Hugging Face Published
Licence Modified MIT, MaaS excluded Flagship terms unstated, Flash is MIT
Hosted price $0.70 / $2.10 per million $0.15 / $0.50 on Flash

If you pay per token

Token efficiency is the entire argument. Equal quality at 47% fewer tokens is a near-halving of the bill on agentic workloads, where a single task can run to six figures of tokens. At $0.70 input and $2.10 output, Mistral Large 4 is not the cheapest per million, but cost per task is the number that decides agent economics.

If you self-host

The calculation inverts. A trillion-parameter model needs serious hardware whatever its token efficiency, and GLM-5.3-Flash at 320B total with 18B active fits far smaller machines. If your constraint is GPUs rather than API spend, the token saving buys you nothing.

The licence difference matters more than the benchmarks

Mistral Large 4 ships under the Mistral Ecosystem Open-Weight licence, a modified MIT. You can use, modify, fine-tune and commercialise it — unless you operate a Model-as-a-Service offering, in which case you need a separate commercial licence from Mistral. If you resell inference, that clause is the deciding factor.

GLM-5.3’s flagship terms remain unstated, while GLM-5.3-Flash is MIT. What to check before you build on any of them.

Sources: Mistral AI.

Published 8 November 2026. Every figure above was checked against the reporting linked here on the same day.

⚖ Our Verdict

Mistral Large 4 if you pay per token and run agentic workloads. GLM-5.3-Flash if you self-host and GPUs are the constraint. The MaaS clause decides it if you resell inference.