Llama 4 Maverick vs Qwen3 Max
Llama 4 Maverick (Meta, released 2025-04-05) and Qwen3 Max (Qwen, released 2025-09-23) sit at opposite ends of the price-versus-quality trade-off. Maverick is a mixture-of-experts multimodal model with a 1,048,576-token context window and image input support. Qwen3 Max is text-only, has a 262,144-token window, and posts stronger Design Arena scores across the board. Both run on OpenKey with one API key and a flat 3% fee on top of provider list price.
Spec vs spec
| Spec | Llama 4 Maverick | Qwen3 Max |
|---|---|---|
| Context window | 1.0M | 262K |
| Max output | 16K | 33K |
| Input modalities | text, image | text |
| Output modalities | text | text |
| Knowledge cutoff | Aug 31, 2024 | Jun 30, 2025 |
| Released | Apr 5, 2025 | Sep 23, 2025 |
| Reasoning | — | optional |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
meta-llama/llama-4-maverick
Input · 1M tokens
$0.150 + 3%$0.154
Output · 1M tokens
$0.600 + 3%$0.618
FEE — FLAT, EVERY MODEL3%
qwen/qwen3-max
Input · 1M tokens
$0.780 + 3%$0.803
Output · 1M tokens
$3.90 + 3%$4.02
Cache read · 1M tokens
$0.156 + 3%$0.161
Cache write · 1M tokens
$0.975 + 3%$1.00
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
meta-llama/llama-4-maverickCheaper
$2.78
$2.70 provider + 3%
qwen/qwen3-max
$16.07
$15.60 provider + 3%
Benchmarks
Design Arena categories where both models have results. Higher Elo and lower rank win.
| Llama 4 Maverick | Qwen3 Max | |||
|---|---|---|---|---|
| Category | Elo | Rank | Elo | Rank |
| 3D | 976 | #91 | 1150 | #62 |
| Code | 929 | #102 | 1159 | #66 |
| Data viz | 926 | #100 | 1149 | #64 |
| Game dev | 903 | #103 | 1160 | #62 |
| UI components | 955 | #94 | 1132 | #67 |
| Websites | 914 | #105 | 1161 | #66 |
Head-to-head preference voting. How we filter and rank
Pricing math
Provider list price for Maverick is $0.15/M input and $0.60/M output; OpenKey adds 3% flat, landing at $0.1545/M input and $0.618/M output. Qwen3 Max lists at $0.78/M input and $3.90/M output, and becomes $0.8034/M input and $4.017/M output on OpenKey. Run the numbers on a 10M-input / 2M-output workload: Maverick costs $2.7 total, Qwen3 Max costs $15.6 — a 5.8x gap. The input price ratio alone is 0.19 (Maverick's input price is about a fifth of Qwen3 Max's). Qwen3 Max also offers cache pricing ($0.156/M cache read, $0.975/M cache write) that Maverick doesn't have listed, which can narrow the gap on repeated-context workloads.
Design Arena performance
Qwen3 Max outranks Maverick in every overlapping category. On codecategories, Qwen3 Max ranks 66 (elo 1159) versus Maverick's rank 102 (elo 929). On dataviz, Qwen3 Max ranks 64 (elo 1149) versus Maverick's rank 100 (elo 926). On gamedev, Qwen3 Max ranks 62 (elo 1160) versus Maverick's rank 103 (elo 903). On uicomponent, Qwen3 Max ranks 67 (elo 1132) versus Maverick's rank 94 (elo 955). On website, Qwen3 Max ranks 66 (elo 1161) versus Maverick's rank 105 (elo 914). Qwen3 Max also has scores in asciiart (rank 32) and svg (rank 60) that Maverick isn't scored on. Maverick has an artificial_analysis intelligence index of 14.3, coding index of 16.3, and agentic index of 1.3 — Qwen3 Max has no artificial_analysis scores in this dataset.
Context and modality
Maverick's context window is 1,048,576 tokens, 4x Qwen3 Max's 262,144 tokens. Maverick also accepts image input (text+image->text) while Qwen3 Max is text-only (text->text). Maverick's max completion is 16,384 tokens; Qwen3 Max's is 32,768, double Maverick's ceiling on a single response. If your workload involves ingesting large codebases, long PDFs, or multi-document context, Maverick's window gives you more room before you have to chunk. If you need vision input at all, Qwen3 Max is off the table.
Knowledge cutoff and recency
Qwen3 Max has a knowledge cutoff of 2025-06-30, about 10 months newer than Maverick's 2024-08-31 cutoff. Qwen3 Max was also released more recently (2025-09-23 versus 2025-04-05). If a task depends on knowing about recent events, libraries, or APIs, Qwen3 Max's fresher training data is the safer bet regardless of the cost difference.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume batch text processing | Llama 4 Maverick | $2.7 vs $15.6 for a 10M-in/2M-out workload |
| Long-document or large-codebase analysis | Llama 4 Maverick | 1,048,576-token context is 4x Qwen3 Max's window |
| UI component or web design generation | Qwen3 Max | Ranks 66-67 vs Maverick's 94-105 in those Design Arena categories |
| Image understanding tasks | Llama 4 Maverick | Only Maverick accepts image input; Qwen3 Max is text-only |
| Coding categories benchmark performance | Qwen3 Max | Elo 1159 (rank 66) vs Maverick's elo 929 (rank 102) |
| Tasks needing latest knowledge | Qwen3 Max | Knowledge cutoff 2025-06-30 vs Maverick's 2024-08-31 |
Questions
- Which model is cheaper to run at scale?
- Llama 4 Maverick, by a wide margin. On a 10M-input/2M-output workload it costs $2.7 on OpenKey versus $15.6 for Qwen3 Max — Maverick's input price alone is roughly 0.19x Qwen3 Max's ($0.1545/M vs $0.8034/M).
- Which model has a bigger context window?
- Llama 4 Maverick, at 1,048,576 tokens versus Qwen3 Max's 262,144 tokens — a 4x difference. That matters for feeding in large codebases or long documents without chunking.
- Does either model support images?
- Only Llama 4 Maverick. It's text+image->text, while Qwen3 Max is text->text only. If your pipeline needs vision input, Maverick is the only option of these two.
- Which model scores higher on Design Arena benchmarks?
- Qwen3 Max, across every shared category. For example on gamedev it ranks 62 (elo 1160) versus Maverick's rank 103 (elo 903), and on website it ranks 66 (elo 1161) versus Maverick's rank 105 (elo 914).