DeepSeek-V4.1-FlashvsGLM-5.3-Flash
DeepSeek-V4.1-Flash | 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 | ||
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. | — | $0.075DeepInfra |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $0.25DeepInfra |
| 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. | 74.2% | 63.4% |
NL2Repo-BenchRepo-level code generation — Tests whether the AI can turn a natural-language requirement into working code across an entire repository, not just produce a single function or patch. Higher is better. | 65.4% | 56.3% |
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. | 90.6% | 84.3% |
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. | 63.9% | 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. | 31.8% | 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. | 54.8% | 48.8% |
Chartography · with toolsChart tasks — A chart-centred test run with tools available to the AI, reported separately from the chart-reading benchmarks above it. Higher is better. | 78.9% | 78% |
| BenchmarksPublished by one model only | ||
Terminal-Bench 4.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Version 4.0 recalibrated how much time, CPU and memory each task gets, removed eight tasks and fixed nineteen, so fewer runs fail for reasons that have nothing to do with the model. Scores are not comparable with earlier versions. Higher is better. | 31.2% | — |
Terminal-Bench 3.0Agentic terminal coding — command-line task completion (v3.0, much harder task set) | 30% | — |
Toolathlon-VerifiedPersonal tool use — Tests how well the AI uses everyday personal tools and apps to get things done — a human-checked version of Toolathlon. Higher is better. | — | 78.4% |
CyberGymCybersecurity — Tests the AI on cybersecurity challenges — finding and exploiting software weaknesses inside a safe sandbox. Higher is better. | 88.1% | — |
Humanity's Last Exam · no toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | 36.8% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 90.9% | — |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | — | 1773 |
CharXiv Reasoning · with toolsChart reasoning — The same chart-and-figure reasoning test, run with the AI allowed to use tools — writing code to inspect the image, for instance — rather than reading the chart unaided. Scores run higher than the unaided version, so read the two as separate tests. Higher is better. | — | 89.4% |
OfficeQA ProDocument Q&A — Questions about office documents, where answering depends on reading the page as a document — layout, tables and figures included — rather than as loose text. Higher is better. | — | 62.4% |
MVBenchVideo understanding — Video questions that cannot be answered from any single frame: the AI has to follow what changes over time — the order things happen in, what moved where. Higher is better. | — | 77.8% |
MMVUVideo reasoning — Expert-level video questions drawn from specific disciplines, where answering means applying subject knowledge to what is happening on screen rather than just describing it. Higher is better. | — | 80.5% |
BabyVisionVisual reasoning — Tests core visual reasoning — seeing and understanding images the way even young children can, which AIs often find surprisingly hard. Higher is better. | — | 53.4% |
threejsevalCommunity preference (Three.js) — Every model gets the same prompt — "the Eiffel Tower", "a glass fishbowl", "a robot arm picking toys into a box" — and builds a 3D scene in Three.js. Real people then see two scenes side by side, names hidden, and vote for the one they prefer. The votes become a chess-style Elo rating on threejseval.com, averaged across all the prompts. It measures whether the scene looks and moves right to a human eye, not whether the code passes a test. Higher is better. | — | 1502 |
| Overview | ||
| Company | DeepSeek | Z.ai |
| Release date | Sep 10 2026 | Aug 26 2026 |
| Access | Proprietary | Open Weight |
Other comparisons
DeepSeek-V4.1-FlashvsClaude Fable 5.1GLM-5.3-FlashvsClaude Fable 5.1DeepSeek-V4.1-FlashvsGPT-6 AstraGLM-5.3-FlashvsGPT-6 AstraDeepSeek-V4.1-FlashvsGemini 3.8 FlashGLM-5.3-FlashvsGemini 3.8 FlashDeepSeek-V4.1-FlashvsMuse Spark 1.3GLM-5.3-FlashvsMuse Spark 1.3DeepSeek-V4.1-FlashvsGrok 4.6GLM-5.3-FlashvsGrok 4.6DeepSeek-V4.1-FlashvsMistral Medium 3.5GLM-5.3-FlashvsMistral Medium 3.5
Frequently asked questions
DeepSeek-V4.1-Flash leads GLM-5.3-Flash on 7 of the 7 benchmarks they both report. GLM-5.3-Flash shipped 15 days before DeepSeek-V4.1-Flash, so benchmark comparisons should account for the intervening progress.
DeepSeek-V4.1-Flash is proprietary, while GLM-5.3-Flash is open weight.
On DeepSWE 1.1, DeepSeek-V4.1-Flash leads at 74.2% vs GLM-5.3-Flash at 63.4%. On NL2Repo-Bench, DeepSeek-V4.1-Flash leads at 65.4% vs GLM-5.3-Flash at 56.3%. On Terminal-Bench 2.1, DeepSeek-V4.1-Flash leads at 90.6% vs GLM-5.3-Flash at 84.3%. On Humanity's Last Exam · with tools, DeepSeek-V4.1-Flash leads at 63.9% vs GLM-5.3-Flash at 55.3%. On Agent's Last Exam · pass@1, DeepSeek-V4.1-Flash leads at 31.8% vs GLM-5.3-Flash at 26.3%. On AutomationBench, DeepSeek-V4.1-Flash leads at 54.8% vs GLM-5.3-Flash at 48.8%. On Chartography · with tools, DeepSeek-V4.1-Flash leads at 78.9% vs GLM-5.3-Flash at 78%.