Grok 4.6vsGLM-5.3-Flash
Grok 4.6 | GLM-5.3-Flash | |
|---|---|---|
| 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. | — | 320B |
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 |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $2.00 | — |
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. | $6.00 | — |
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. | $0.50 | — |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $2.20Amazon Bedrock | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $6.60Amazon Bedrock | — |
| Benchmarks | ||
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | 65.9% | 63.4% |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | 1753 | 1773 |
| 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. | 65% | — |
FrontierCode v1.1 (Extended) · extended splitAgentic coding — frontier-difficulty agentic coding tasks (v1.1, extended split) | 61.3% | — |
APEX-SWEExpert software engineering — expert-level software-engineering tasks (AI Productivity Index) | 56.4% | — |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 92% | — |
Terminal-Bench 3.0Agentic terminal coding — command-line task completion (v3.0, much harder task set) | 26% | — |
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. | — | 84.3% |
APEX-AgentsExpert agentic work — expert-level agentic work tasks (AI Productivity Index) | 57.5% | — |
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. | — | 55.3% |
Agent's Last Exam · pass@1Agentic computer use — A hard set of desktop and operating-system tasks an AI agent has to finish by looking at the screen and working the machine itself. The score is the share it passes outright — partial credit does not count. Higher is better. | — | 26.3% |
AutomationBenchBusiness workflows — Tests whether the AI can run real multi-step business workflows — the kind of end-to-end office processes companies want to automate — from start to finish. Higher is better. | — | 48.8% |
Harvey's Legal Agent BenchmarkAgentic legal work — Harvey's test of whether an AI agent can complete real legal work — drafting and reviewing documents, working with spreadsheets and presentations, and navigating files the way a lawyer's assistant would. Higher is better. | 15.8% | — |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | 61 | — |
AA-BriefcaseKnowledge work — Artificial Analysis agentic office-work eval (Elo) | 1577 | — |
| Overview | ||
| Company | SpaceXAI | Z.ai |
| Release date | Aug 12 2026 | Aug 26 2026 |
| Access | Proprietary | Open Weight |
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Frequently asked questions
Grok 4.6 and GLM-5.3-Flash are evenly matched across the 2 benchmarks they both report (DeepSWE 1.1, GDPval-AA v2). Only Grok 4.6 has a verified first-party API price: $2.00 per million input tokens and $6.00 per million output tokens. No pay-as-you-go API rate is tracked for GLM-5.3-Flash. Grok 4.6 shipped 14 days before GLM-5.3-Flash, so benchmark comparisons should account for the intervening progress.
Grok 4.6 is proprietary, while GLM-5.3-Flash is open weight.
On DeepSWE 1.1, Grok 4.6 leads at 65.9% vs GLM-5.3-Flash at 63.4%. On GDPval-AA v2, GLM-5.3-Flash leads at 1773 vs Grok 4.6 at 1753.
Grok 4.6 was released by SpaceXAI on Aug 12 2026.
GLM-5.3-Flash was released by Z.ai on Aug 26 2026.
Grok 4.6 leads on DeepSWE 1.1 — Grok 4.6 65.9% vs GLM-5.3-Flash 63.4%.
Only Grok 4.6 has a verified first-party API price: $2.00 per million input tokens and $6.00 per million output tokens. No pay-as-you-go API rate is tracked for GLM-5.3-Flash. Rates are pay-as-you-go API prices verified on August 18, 2026.
Grok 4.6 is a proprietary model released by SpaceXAI. GLM-5.3-Flash is an open weight model released by Z.ai.