Compare AI models
| Specifications | ||
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 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. | $0.50 | $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. | $3.00 | $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 every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.325Alibaba | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $1.95Alibaba | — |
| $163Alibaba | $375SpaceXSI list price | |
| 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. | 72% | 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. | 78.8% | 76.7% |
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. | 28.8% | — |
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% |
| Overview | ||
| Company | Qwen | SpaceXSI |
| Release date | Apr 2 2026 | Feb 17 2026 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Qwen3.6-PlusvsClaude Haiku 5.5Grok 4.20 BetavsClaude Haiku 5.5Qwen3.6-PlusvsGPT-6.1 TerraGrok 4.20 BetavsGPT-6.1 TerraQwen3.6-PlusvsGemini 4 CarbonGrok 4.20 BetavsGemini 4 CarbonQwen3.6-PlusvsMuse Spark OpenGrok 4.20 BetavsMuse Spark OpenQwen3.6-PlusvsDeepSeek-V4.1-Flash-1017Grok 4.20 BetavsDeepSeek-V4.1-Flash-1017Qwen3.6-PlusvsMistral Large 4Grok 4.20 BetavsMistral Large 4Frequently asked questions
Qwen3.6-Plus leads Grok 4.20 Beta on 2 of the 2 benchmarks they both report (BullshitBench v2, SWE-Bench Verified). Qwen3.6-Plus is cheaper on input: $0.50 vs $1.25 per million tokens. Grok 4.20 Beta is cheaper on output: $2.50 vs $3.00 per million tokens. Figures are base-tier rates. Grok 4.20 Beta shipped 44 days before Qwen3.6-Plus, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On BullshitBench v2, Qwen3.6-Plus leads at 72% vs Grok 4.20 Beta at 56%. On SWE-Bench Verified, Qwen3.6-Plus leads at 78.8% vs Grok 4.20 Beta at 76.7%.