Claude Mythos 5vsGLM-4.5
Claude Mythos 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. | — | 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. | 1M | 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. | — | $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. | — | $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. | 95.5% | 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% |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | 88% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 88% | — |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 64.5% | — |
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% |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 85% | — |
| Overview | ||
| Company | Anthropic | Z.ai |
| Release date | Jun 9 2026 | Jul 28 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
Frequently asked questions
Claude Mythos 5 leads GLM-4.5 on 1 of the 1 benchmark they both report (SWE-Bench Verified). Only GLM-4.5 has a verified first-party API price: $0.60 per million input tokens and $2.20 per million output tokens. No pay-as-you-go API rate is tracked for Claude Mythos 5. GLM-4.5 shipped 316 days before Claude Mythos 5, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5) vs 128k (GLM-4.5). Claude Mythos 5 is proprietary, while GLM-4.5 is open weight.
On SWE-Bench Verified, Claude Mythos 5 leads at 95.5% vs GLM-4.5 at 64.2%.
Claude Mythos 5 was released by Anthropic on Jun 9 2026.
GLM-4.5 was released by Z.ai on Jul 28 2025.
Claude Mythos 5 leads on SWE-Bench Verified — Claude Mythos 5 95.5% vs GLM-4.5 64.2%.
Only GLM-4.5 has a verified first-party API price: $0.60 per million input tokens and $2.20 per million output tokens. No pay-as-you-go API rate is tracked for Claude Mythos 5. Rates are pay-as-you-go API prices verified on August 18, 2026.
Claude Mythos 5 has a 1M context window; GLM-4.5 has 128k.
Claude Mythos 5 is a proprietary model released by Anthropic. GLM-4.5 is an open weight model released by Z.ai.