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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
98 tok/s
TTFT
0.83s

Winner by Category

Cheaper
Llama 4 Maverick
Faster (tok/s)
Llama 4 Maverick
Lower Latency
Llama 4 Maverick
Benchmarks (1-1)
Tie

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
98 tok/s
Time to First Token (seconds) — lower is better
QwQ 32B
—
Llama 4 Maverick
0.83s

Editorial Analysis

Verdict. QwQ 32B and Llama 4 Maverick split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.

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 (9.5). Llama 4 Maverick leads on Coding Index (16.3), Intelligence Index (9.3).

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.

Head-to-head deltas

  • Benchmark wins tie exactly at 1–1. The tiebreaker on raw benchmark parity will be price, speed, or capability coverage.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
9.59.3
Coding Index
—16.3
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
QwQ 32B1 wins
1 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?

It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Llama 4 Maverick generates tokens faster at 98 tok/s vs — tok/s. However, Llama 4 Maverick has lower time-to-first-token (0.83s vs —s).

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

Choose based on your priorities: Llama 4 Maverick for lower cost, both perform similarly on benchmarks, and Llama 4 Maverick for faster generation. For latency-sensitive apps, check the TTFT comparison above.