Qwen3.5vsGrok 4.20 Beta
Qwen3.5 | Grok 4.20 Beta | |
|---|---|---|
| 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. | 397B | — |
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. | $0.60 | $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. | $3.60 | $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. | — | $0.20 |
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. | $0.08Darkbloom | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.15DeepInfra | — |
| 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. | 76.4% | 76.7% |
| 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. | — | 56% |
SWE-Bench MultilingualMultilingual coding — Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | 69.3% | — |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | 52.5% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 69% | — |
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. | 28.7% | — |
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. | — | 53.3% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 88.4% | — |
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. | 62.2% | — |
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better. | 80.8% | — |
MMMU-ProMultimodal reasoning — A tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 79% | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | 85% | — |
| Overview | ||
| Company | Qwen | SpaceXAI |
| Release date | Feb 16 2026 | Feb 17 2026 |
| Access | Open Weight | Proprietary |
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Frequently asked questions
Grok 4.20 Beta leads Qwen3.5 on 1 of the 1 benchmark they both report (SWE-Bench Verified). Qwen3.5 is cheaper on input: $0.60 vs $1.25 per million tokens. Grok 4.20 Beta is cheaper on output: $2.50 vs $3.60 per million tokens. Figures are base-tier rates. Qwen3.5 shipped 1 days before Grok 4.20 Beta, so benchmark comparisons should account for the intervening progress.
Qwen3.5 is open weight, while Grok 4.20 Beta is proprietary.
On SWE-Bench Verified, Grok 4.20 Beta leads at 76.7% vs Qwen3.5 at 76.4%.
Qwen3.5 was released by Qwen on Feb 16 2026.
Grok 4.20 Beta was released by SpaceXAI on Feb 17 2026.
Grok 4.20 Beta leads on SWE-Bench Verified — Qwen3.5 76.4% vs Grok 4.20 Beta 76.7%.
Qwen3.5 is cheaper on input: $0.60 vs $1.25 per million tokens. Grok 4.20 Beta is cheaper on output: $2.50 vs $3.60 per million tokens. Figures are base-tier rates. Rates are pay-as-you-go API prices verified on August 18, 2026.
Qwen3.5 is an open weight model released by Qwen. Grok 4.20 Beta is a proprietary model released by SpaceXAI.