Compare/QwQ 32B vs Llama 4 Maverick

QwQ 32BvsLlama 4 Maverick

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Alibaba

QwQ 32B

Input
$0.66/M
Output
$1/M
Speed
TTFT
Meta

Llama 4 Maverick

Input
$0.26/M
Output
$0.91/M
Speed
96 tok/s
TTFT
0.93s

Winner by Category

Cheaper
Llama 4 Maverick
Faster (tok/s)
Llama 4 Maverick
Lower Latency
Llama 4 Maverick
Benchmarks (0-2)
Llama 4 Maverick

Pricing Comparison

MetricQwQ 32BLlama 4 Maverick
Input ($/M tokens)$0.66$0.26
Output ($/M tokens)$1$0.91
Cost for 1M input + 100K output tokens:
QwQ 32B$0.76
Llama 4 Maverick$0.35

Speed Comparison

Output Speed (tokens/s) — higher is better
QwQ 32B
Llama 4 Maverick
96 tok/s
Time to First Token (seconds) — lower is better
QwQ 32B
Llama 4 Maverick
0.93s

Editorial Analysis

Verdict. Llama 4 Maverick takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.

Pricing. Both models sit in the budget bracket for output-token pricing. At 1.1× the per-million-token cost, Llama 4 Maverick is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Llama 4 Maverick makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. QwQ 32B is strongest on Intelligence Index (13.4). Llama 4 Maverick leads on Coding Index (16.3), Intelligence Index (14.5).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. Alibaba and Meta sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while Meta often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): QwQ 32B costs $34.80 ($418/year); Llama 4 Maverick costs $21.45 ($257/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): QwQ 32B ≈ $5.30/run, Llama 4 Maverick ≈ $3.12/run. At agent/realtime scale (200M input / 100M output per million requests): QwQ 32B ≈ $232/run, Llama 4 Maverick ≈ $143/run. Llama 4 Maverick becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
13.414.5
Coding Index
16.3
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
QwQ 32B0 wins
2 winsLlama 4 Maverick

Frequently Asked Questions

Which is cheaper, QwQ 32B or Llama 4 Maverick?

Llama 4 Maverick is cheaper overall. Its blended price (3:1 input/output ratio) is $0.42/M tokens vs $0.74/M for QwQ 32B.

Which model performs better on benchmarks?

Llama 4 Maverick wins 2 out of 12 benchmarks compared to 0 for QwQ 32B. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Llama 4 Maverick generates tokens faster at 96 tok/s vs — tok/s. However, Llama 4 Maverick has lower time-to-first-token (0.93s vs —s).

When should I use QwQ 32B vs Llama 4 Maverick?

Choose based on your priorities: Llama 4 Maverick for lower cost, Llama 4 Maverick for stronger benchmark performance, and Llama 4 Maverick for faster generation. For latency-sensitive apps, check the TTFT comparison above.