Compare/Llama 4 Maverick vs DeepSeek V3 (Dec '24)

Llama 4 MaverickvsDeepSeek V3 (Dec '24)

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

Meta

Llama 4 Maverick

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

DeepSeek V3 (Dec '24)

Input
$0.36/M
Output
$0.89/M
Speed
TTFT

Winner by Category

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

Pricing Comparison

MetricLlama 4 MaverickDeepSeek V3 (Dec '24)
Input ($/M tokens)$0.26$0.36
Output ($/M tokens)$0.91$0.89
Cost for 1M input + 100K output tokens:
Llama 4 Maverick$0.35
DeepSeek V3 (Dec '24)$0.45

Speed Comparison

Output Speed (tokens/s) — higher is better
Llama 4 Maverick
96 tok/s
DeepSeek V3 (Dec '24)
Time to First Token (seconds) — lower is better
Llama 4 Maverick
0.93s
DeepSeek V3 (Dec '24)

Editorial Analysis

Verdict. Llama 4 Maverick and DeepSeek V3 (Dec '24) 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 1.0× the per-million-token cost, DeepSeek V3 (Dec '24) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). DeepSeek V3 (Dec '24) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Llama 4 Maverick is strongest on Coding Index (16.3), Intelligence Index (14.5). DeepSeek V3 (Dec '24) leads on Coding Index (23.0), Intelligence Index (14.2).

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

Provider. Meta and DeepSeek sell to overlapping but distinct developer audiences: Meta tends to ship frontier reasoning models with premium positioning, while DeepSeek 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): Llama 4 Maverick costs $21.45 ($257/year); DeepSeek V3 (Dec '24) costs $24.15 ($290/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Llama 4 Maverick ≈ $3.12/run, DeepSeek V3 (Dec '24) ≈ $3.58/run. At agent/realtime scale (200M input / 100M output per million requests): Llama 4 Maverick ≈ $143/run, DeepSeek V3 (Dec '24) ≈ $161/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
14.514.2
Coding Index
16.323.0
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Llama 4 Maverick1 wins
1 winsDeepSeek V3 (Dec '24)

Frequently Asked Questions

Which is cheaper, Llama 4 Maverick or DeepSeek V3 (Dec '24)?

Llama 4 Maverick is cheaper overall. Its blended price (3:1 input/output ratio) is $0.42/M tokens vs $0.49/M for DeepSeek V3 (Dec '24).

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 96 tok/s vs — tok/s. Llama 4 Maverick also has lower time-to-first-token (0.93s vs —s).

When should I use Llama 4 Maverick vs DeepSeek V3 (Dec '24)?

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.