Qwen2.5-Max vs Llama 3.1 405B
Qwen vs Meta · Prices checked 12 August 2026
There is a 3.8× price gap here. Llama 3.1 405B blends to $0.800 per million tokens; Qwen2.5-Max to $3.04. A single 100K-input, 10K-output job costs $0.088 on Llama 3.1 405B against $0.224 on Qwen2.5-Max.
Capability favours Qwen2.5-Max, ahead on 4 of 5 suites they both publish. The widest gap is on MATH, where Qwen2.5-Max leads by 12 points. Llama 3.1 405B reads more in one request: 128,000 tokens of context against 32,000.
Pricing and capacity
| Metric | Qwen2.5-Max | Llama 3.1 405B | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.60 | $0.800 | 2.0× |
| Output / 1M tokens | $6.40 | $0.800 | 8.0× |
| Blended · 70/30calculated | $3.04 | $0.800 | 3.8× |
| Blended · 50/50calculated | $4.00 | $0.800 | 5.0× |
| Blended · 80/20calculated | $2.56 | $0.800 | 3.2× |
| Blended · 20/80calculated | $5.44 | $0.800 | 6.8× |
| Job cost · 100K + 10Kcalculated | $0.224 | $0.088 | 2.5× |
| Job cost · 1M + 100Kcalculated | $2.24 | $0.880 | 2.5× |
| Context window | 32,000 | 128,000 | 4.0× |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
| Benchmark | Qwen2.5-Max | Llama 3.1 405B | Leader |
|---|---|---|---|
| MMLU | 87% | 88% | Llama 3.1 405B |
| GPQA Diamond | 60% | 51% | Qwen2.5-Max |
| MATH | 85% | 73% | Qwen2.5-Max |
| HumanEval | 90% | 89% | Qwen2.5-Max |
| LMArena Elo | 1296 Elo | 1290 Elo | Qwen2.5-Max |
Only suites both models report are listed, so a missing score is never shown as a loss. Figures are provider-published or from public leaderboards and are not independently re-run.
What each model is for
Qwen2.5-Max
Qwen · Flagship
Alibaba's closed-weights flagship. Frontier-quality MoE that competes with Claude / GPT on Chinese benchmarks at competitive pricing.
- Frontier on Chinese benchmarks
- MoE inference economics
- Strong tool use
- Multilingual
Llama 3.1 405B
Meta · Large
Largest dense Llama. Used as a quality benchmark for open weights, heavy to run, often hosted via Together / DeepInfra / Cerebras.
- Top open-weights quality
- Permissive license
- Strong reasoning
Frequently asked questions
Which is cheaper, Qwen2.5-Max or Llama 3.1 405B?
There is a 3.8× price gap here. Llama 3.1 405B blends to $0.800 per million tokens; Qwen2.5-Max to $3.04. A single 100K-input, 10K-output job costs $0.088 on Llama 3.1 405B against $0.224 on Qwen2.5-Max. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which performs better, Qwen2.5-Max or Llama 3.1 405B?
Capability favours Qwen2.5-Max, ahead on 4 of 5 suites they both publish. The widest gap is on MATH, where Qwen2.5-Max leads by 12 points. These are the figures each provider or public leaderboard publishes, not results we re-run, and a benchmark average can hide the specific behaviour your workload depends on.
Which has the larger context window, Qwen2.5-Max or Llama 3.1 405B?
Llama 3.1 405B reads more in one request: 128,000 tokens of context against 32,000. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare Qwen2.5-Max and Llama 3.1 405B on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.