Compare/Llama 4 Scout vs Granite 4.2 30B

Llama 4 ScoutvsGranite 4.2 30B

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

Meta

Llama 4 Scout

Input
$0.18/M
Output
$0.66/M
Speed
94 tok/s
TTFT
0.82s
IBM

Granite 4.2 30B

Input
$0.16/M
Output
$0.65/M
Speed
76 tok/s
TTFT
0.81s

Winner by Category

Cheaper
Granite 4.2 30B
Faster (tok/s)
Llama 4 Scout
Lower Latency
Granite 4.2 30B
Benchmarks (0-2)
Granite 4.2 30B

Pricing Comparison

MetricLlama 4 ScoutGranite 4.2 30B
Input ($/M tokens)$0.18$0.16
Output ($/M tokens)$0.66$0.65
Cost for 1M input + 100K output tokens:
Llama 4 Scout$0.25
Granite 4.2 30B$0.23

Speed Comparison

Output Speed (tokens/s) — higher is better
Llama 4 Scout
94 tok/s
Granite 4.2 30B
76 tok/s
Time to First Token (seconds) — lower is better
Llama 4 Scout
0.82s
Granite 4.2 30B
0.81s

Editorial Analysis

Verdict. Granite 4.2 30B 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 1.0× the per-million-token cost, Granite 4.2 30B is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Granite 4.2 30B makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Llama 4 Scout is strongest on Intelligence Index (10.3), Coding Index (8.2). Granite 4.2 30B leads on Coding Index (29.9), Intelligence Index (23.7).

Speed. Throughput is comparable — 94 tok/s vs 76 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.

Provider. Meta and IBM sell to overlapping but distinct developer audiences: Meta tends to ship frontier reasoning models with premium positioning, while IBM 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 Scout costs $15.30 ($184/year); Granite 4.2 30B costs $14.55 ($175/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Llama 4 Scout ≈ $2.22/run, Granite 4.2 30B ≈ $2.10/run. At agent/realtime scale (200M input / 100M output per million requests): Llama 4 Scout ≈ $102/run, Granite 4.2 30B ≈ $97/run. Granite 4.2 30B 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
10.323.7
Coding Index
8.229.9
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Llama 4 Scout0 wins
2 winsGranite 4.2 30B

Frequently Asked Questions

Which is cheaper, Llama 4 Scout or Granite 4.2 30B?

Granite 4.2 30B is cheaper overall. Its blended price (3:1 input/output ratio) is $0.28/M tokens vs $0.30/M for Llama 4 Scout.

Which model performs better on benchmarks?

Granite 4.2 30B wins 2 out of 12 benchmarks compared to 0 for Llama 4 Scout. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Llama 4 Scout generates tokens faster at 94 tok/s vs 76 tok/s. However, Granite 4.2 30B has lower time-to-first-token (0.81s vs 0.82s).

When should I use Llama 4 Scout vs Granite 4.2 30B?

Choose based on your priorities: Granite 4.2 30B for lower cost, Granite 4.2 30B for stronger benchmark performance, and Llama 4 Scout for faster generation. For latency-sensitive apps, check the TTFT comparison above.