AI model comparison
Qwen3 235B A22B Instruct 2507 vs Llama 4 Maverick
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass.
- Input / 1M
- $0.09
- Output / 1M
- $0.55
- Context
- 262K
Meta
Llama 4 Maverick
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward
- Input / 1M
- $0.19
- Output / 1M
- $0.65
- Context
- 1.05M
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3 235B A22B Instruct 2507
1.5x cheaper for a typical chat
Higher intelligence score
Qwen3 235B A22B Instruct 2507
12 vs 10 on Artificial Analysis
Larger context window
Llama 4 Maverick
1.05M vs 262K tokens
Newer release
Qwen3 235B A22B Instruct 2507
Released July 21, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3 235B A22B Instruct 250712Coding index
Qwen3 235B A22B Instruct 2507Not availableAgentic index
Qwen3 235B A22B Instruct 2507Not availablePricing
Qwen3 235B A22B Instruct 2507 vs Llama 4 Maverick API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3 235B A22B Instruct 2507 | |
|---|---|---|
| Input tokensPer 1M tokens | $0.09 | $0.19 |
| Output tokensPer 1M tokens | $0.55 | $0.65 |
| Cached input (read)Per 1M tokens | Not available | $0.05 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Qwen3 235B A22B Instruct 2507$0.46Coding task
30K in, 4K out
Qwen3 235B A22B Instruct 2507$4.90Long document summary
150K in, 2K out
Qwen3 235B A22B Instruct 2507$14.60Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3 235B A22B Instruct 2507 | |
|---|---|---|
| Context window | 262K tokens | 1.05M tokens |
| Max output | 16K tokens | 16K tokens |
| Input types | Text | Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | July 21, 2025 | April 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3 235B A22B Instruct 2507 | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Not supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
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- Qwen3 235B A22B Instruct 2507 vs Qwen3 30B A3B
- Llama 4 Maverick vs Gemini 2.5 Flash Lite
- Llama 4 Maverick vs GPT-4o-mini
- Llama 4 Maverick vs Llama 3.3 70B Instruct
- Llama 4 Maverick vs Qwen3 Coder Next
- Llama 4 Maverick vs Qwen3 Next 80B A3B Instruct
- Llama 4 Maverick vs DeepSeek V3 0324
- Llama 4 Maverick vs Mistral Small 4
- Llama 4 Maverick vs GLM 4.5 Air
- Llama 4 Maverick vs Trinity Large Thinking
- Llama 4 Maverick vs Llama 4 Scout
- Llama 4 Maverick vs Llama 3.1 70B Instruct
Our take
Qwen3 235B A22B Instruct 2507 is 1.5x cheaper for a typical chat. Qwen3 235B A22B Instruct 2507 scores higher on the Artificial Analysis Intelligence Index (12 vs 10). Llama 4 Maverick has the larger context window (1.05M vs 262K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Qwen3 235B A22B Instruct 2507 or Llama 4 Maverick cheaper?
Qwen3 235B A22B Instruct 2507 is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3 235B A22B Instruct 2507 costs $0.09 per 1M input tokens and $0.55 per 1M output tokens, while Llama 4 Maverick costs $0.19 per 1M input tokens and $0.65 per 1M output tokens.
Which has a bigger context window, Qwen3 235B A22B Instruct 2507 or Llama 4 Maverick?
Llama 4 Maverick supports up to 1.05M tokens of context, compared with 262K for Qwen3 235B A22B Instruct 2507.
Is Qwen3 235B A22B Instruct 2507 smarter than Llama 4 Maverick?
On the Artificial Analysis Intelligence Index, Qwen3 235B A22B Instruct 2507 scores 12 and Llama 4 Maverick scores 10, putting Qwen3 235B A22B Instruct 2507 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3 235B A22B Instruct 2507 and Llama 4 Maverick at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 235B A22B Instruct 2507 and Llama 4 Maverick answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3 235B A22B Instruct 2507 and Llama 4 Maverick at the same time. Compare the answers side by side and keep the best one.