Verified November 2026

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Llama 4 Maverick vs Qwen 3 32B

A straight cost comparison of Llama 4 Maverick (Meta (Llama)) and Qwen 3 32B (Alibaba (Qwen)), per 1,000,000 tokens, verified November 2026.

$0.27Llama 4 Maverick input / 1M
$0.15Qwen 3 32B input / 1M
38%Blended price gap
Qwen 3 32BCheaper blended

Rate-by-rate comparison

USD per 1M tokens · November 2026
MetricLlama 4 MaverickQwen 3 32BWinner
Input / 1M$0.27$0.15Qwen 3 32B
Cached input / 1M$0.027$0.015Qwen 3 32B
Cache write / 1M——Tie
Output / 1M$0.85$0.60Qwen 3 32B
Context window1,000,000131,072Llama 4 Maverick
Batch APIYesYesTie
Long-context tierNoneNone—

For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.

Blended cost: 1M input + 250K output

ModelBlended costDifference
Llama 4 Maverick$0.483+$0.183
Qwen 3 32B$0.30Cheaper

Ten workloads, two bills

The same two models, priced across ten workloads that differ only in their input:output ratio. Nothing else changes — no retries, no system prompt, no middleware.

WorkloadLlama 4 MaverickQwen 3 32BWinner
Classification
100K reqs · 500 in / 10 out
$14.35$8.10Qwen 3 32B
Data extraction
10K reqs · 2K in / 200 out
$7.10$4.20Qwen 3 32B
Support chat
1K reqs · 4K in / 600 out
$1.59$0.96Qwen 3 32B
Code review
2K reqs · 8K in / 1.5K out
$6.87$4.20Qwen 3 32B
Summarisation
1K reqs · 20K in / 1K out
$6.25$3.60Qwen 3 32B
Agent loop
5K reqs · 12K in / 2K out
$24.70$15Qwen 3 32B
Translation
500 reqs · 15K in / 15K out
$8.40$5.63Qwen 3 32B
Long-document QA
200 reqs · 120K in / 800 out
$6.62$3.70Qwen 3 32B
Cached RAG
1K reqs · 50K in (45K cached) / 1K out
$3.43$2.03Qwen 3 32B
Nightly batch
10K reqs · 10K in / 2K out
$22$13.50Qwen 3 32B

Llama 4 Maverick wins 0 of 10, Qwen 3 32B wins 10 of 10. The winner is set by the token mix, not by the headline rate.

Where the two bills cross over

Qwen 3 32B is cheaper on both sides of the mix: $0.15 vs $0.27 per million input tokens, and $0.60 vs $0.85 per million output. No input:output ratio reverses that, so on price alone the other model never becomes the better choice — it has to win on context, latency or output quality.

Cost at four scales

The same support-chat workload (4K input, 600 output per request) at four monthly volumes.

Requests / monthLlama 4 MaverickQwen 3 32BDifference
100$0.159$0.096Qwen 3 32B cheaper by $0.063
1,000$1.59$0.96Qwen 3 32B cheaper by $0.63
10,000$15.90$9.60Qwen 3 32B cheaper by $6.30
100,000$159$96Qwen 3 32B cheaper by $63

What caching does to each bill

Caching only helps the part of the prompt that repeats. This is the support-chat workload (1,000 requests, 4,000 input tokens each) with an increasing share of that prompt served from a warm cache, written once on the first request.

Cached share of the promptLlama 4 MaverickQwen 3 32BWinner
0%$1.59$0.96Qwen 3 32B
50%$1.10$0.69Qwen 3 32B
80%$0.813$0.528Qwen 3 32B
95%$0.668$0.448Qwen 3 32B

Both models publish a cached-read rate, so the discount is comparable: Llama 4 Maverick reads cache at $0.027 per million, Qwen 3 32B at $0.015.

Which one should you pick?

Llama 4 Maverick wins on none of the ten workloads above, while Qwen 3 32B wins on classification, data extraction, support chat, code review, summarisation, agent loop, translation, long-document qa, cached rag, nightly batch.

Beyond price, the two differ on input rate ($0.27 vs $0.15); output rate ($0.85 vs $0.60); cached-input rate ($0.027 vs $0.015); context window (1,000,000 vs 131,072).

Batch mode is available on Llama 4 Maverick and Qwen 3 32B, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.

FAQ

Is Llama 4 Maverick cheaper than Qwen 3 32B?

On a blended 1M-input-plus-250K-output workload, Qwen 3 32B is cheaper by 38% ($0.30 vs $0.483). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.

Which handles longer prompts, Llama 4 Maverick or Qwen 3 32B?

Qwen 3 32B has the larger context window (1,000,000 vs 131,072 tokens). Neither model publishes a long-context surcharge.

Do both models support prompt caching?

Llama 4 Maverick bills cached reads at $0.027 per 1M; Qwen 3 32B at $0.015.

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