LLaMA 3.3vsQwen3-Coder
LLaMA 3.3 | Qwen3-Coder | |
|---|---|---|
| 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. | 70B | 480B |
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. | — | 256k |
| 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. | — | $1.00 |
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. | — | $5.00 |
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. | $0.10DeepInfra | $0.22Google |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.32DeepInfra | $1.55Novita |
| 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. | — | 20% |
| Overview | ||
| Company | Meta | Qwen |
| Release date | Dec 6 2024 | Jul 22 2025 |
| Access | Open Weight | Open Weight |
Other comparisons
LLaMA 3.3vsClaude Fable 5.1Qwen3-CodervsClaude Fable 5.1LLaMA 3.3vsGPT-6 AstraQwen3-CodervsGPT-6 AstraLLaMA 3.3vsGemini 3.8 FlashQwen3-CodervsGemini 3.8 FlashLLaMA 3.3vsGrok 4.6Qwen3-CodervsGrok 4.6LLaMA 3.3vsDeepSeek-V4.1-FlashQwen3-CodervsDeepSeek-V4.1-FlashLLaMA 3.3vsMistral Medium 3.5Qwen3-CodervsMistral Medium 3.5
Frequently asked questions
LLaMA 3.3 and Qwen3-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3-Coder has a verified first-party API price: $1.00 per million input tokens and $5.00 per million output tokens. No pay-as-you-go API rate is tracked for LLaMA 3.3. LLaMA 3.3 shipped 228 days before Qwen3-Coder, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while Qwen3-Coder has 480B.
Direct benchmark comparisons are unavailable — LLaMA 3.3 and Qwen3-Coder don't publish scores on any of the same benchmarks.