Compare AI models
| 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. | $0.66 | $1.25 |
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. | $1.98 | $2.50 |
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. | $0.022 | $0.20 |
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. | $0.2254Wafer | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $1.98DeepSeek | — |
| Benchmarks | ||
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. | 35% | 56% |
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. | 80.6% | 76.7% |
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 61.3% | 53.3% |
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. | 87.9% | — |
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. | 74.1% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 83.4% | — |
CyberGymCybersecurity — Tests the AI on cybersecurity challenges — finding and exploiting software weaknesses inside a safe sandbox. Higher is better. | 83.3% | — |
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. | 42.7% | — |
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. | 60% | — |
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. | 31.8% | — |
| Overview | ||
| Company | DeepSeek | SpaceXAI |
| Release date | Aug 13 2026 | Feb 17 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek-V4-Pro-0813vsClaude Sonnet 5.5Grok 4.20 BetavsClaude Sonnet 5.5DeepSeek-V4-Pro-0813vsGPT-6 SolGrok 4.20 BetavsGPT-6 SolDeepSeek-V4-Pro-0813vsGemini 3.8 FlashGrok 4.20 BetavsGemini 3.8 FlashDeepSeek-V4-Pro-0813vsMuse Spark 1.3Grok 4.20 BetavsMuse Spark 1.3DeepSeek-V4-Pro-0813vsMistral Medium 3.5Grok 4.20 BetavsMistral Medium 3.5DeepSeek-V4-Pro-0813vsKimi K3Grok 4.20 BetavsKimi K3Frequently asked questions
DeepSeek-V4-Pro-0813 leads Grok 4.20 Beta on 2 of the 3 benchmarks they both report (BullshitBench v2, SWE-Bench Verified, ARC-AGI-2). DeepSeek-V4-Pro-0813 is cheaper on both input and output: $0.66 vs $1.25 per million input tokens, and $1.98 vs $2.50 per million output tokens. Figures are base-tier rates. Grok 4.20 Beta shipped 177 days before DeepSeek-V4-Pro-0813, so benchmark comparisons should account for the intervening progress.
DeepSeek-V4-Pro-0813 is open weight, while Grok 4.20 Beta is closed.
On BullshitBench v2, Grok 4.20 Beta leads at 56% vs DeepSeek-V4-Pro-0813 at 35%. On SWE-Bench Verified, DeepSeek-V4-Pro-0813 leads at 80.6% vs Grok 4.20 Beta at 76.7%. On ARC-AGI-2, DeepSeek-V4-Pro-0813 leads at 61.3% vs Grok 4.20 Beta at 53.3%.