Mistral Medium 3.5vsGLM-4.5
Mistral Medium 3.5 | GLM-4.5 | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 128B | 355B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 256k | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $1.50 | $0.60 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $7.50 | $2.20 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | — | $0.11 |
| Benchmarks | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 77.6% | 64.2% |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 8% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 79.1% |
| Overview | ||
| Company | Mistral | Z.ai |
| Release date | Apr 29 2026 | Jul 28 2025 |
| Access | Open Weight | Open Weight |
Other comparisons
Mistral Medium 3.5vsClaude Fable 5.1GLM-4.5vsClaude Fable 5.1Mistral Medium 3.5vsGPT-6 AstraGLM-4.5vsGPT-6 AstraMistral Medium 3.5vsGemini 3.8 FlashGLM-4.5vsGemini 3.8 FlashMistral Medium 3.5vsMuse Spark 1.3GLM-4.5vsMuse Spark 1.3Mistral Medium 3.5vsGrok 4.6GLM-4.5vsGrok 4.6Mistral Medium 3.5vsDeepSeek-V4.1-FlashGLM-4.5vsDeepSeek-V4.1-Flash
Frequently asked questions
Mistral Medium 3.5 leads GLM-4.5 on 1 of the 1 benchmark they both report (SWE-Bench Verified). GLM-4.5 is cheaper on both input and output: $0.60 vs $1.50 per million input tokens, and $2.20 vs $7.50 per million output tokens. GLM-4.5 shipped 275 days before Mistral Medium 3.5, so benchmark comparisons should account for the intervening progress.
Mistral Medium 3.5 has 128B parameters, while GLM-4.5 has 355B. Context windows are 256k (Mistral Medium 3.5) vs 128k (GLM-4.5).
On SWE-Bench Verified, Mistral Medium 3.5 leads at 77.6% vs GLM-4.5 at 64.2%.