💰 Unit Cost Winner Gemma 4 31B IT $0.12/1M in · $0.36/1M out
⚡ Latency & Speed Winner Gemma 4 31B IT 115ms TTFT · 155 tok/s
💻 Coding (SWE) Winner Gemma 4 31B IT 59.2% SWE-bench · 91.8% HumanEval
🧠 STEM Reasoning Winner Gemma 4 31B IT 71.2% GPQA · 91.5% MATH-500

Which model is better: Gemma 4 31B IT or Llama 3.3 70B Instruct?

Gemma 4 31B IT and Llama 3.3 70B Instruct share identical input pricing at $0.12 per 1M tokens ($0.36 vs. $0.30 output). In terms of operational performance, Gemma 4 31B IT delivers lower response latency at 115ms TTFT (30ms faster than Llama 3.3 70B Instruct) with 155 vs. 165 tok/s throughput. Gemma 4 31B IT leads coding evaluations at 59.2% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 71.2% vs. 55.6% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.

Verified Performance & Unit Economics Delta (12 Dimensions)

Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.

Metric / Dimension Gemma 4 31B IT Llama 3.3 70B Instruct Net Delta / Advantage
Input Cost / 1M Tokens $0.12 $0.12 Identical Pricing
Output Cost / 1M Tokens $0.36 $0.30 Llama 3.3 70B Instruct (16.7% lower)
Prompt Cache Read / 1M $0.030 $0.030 Identical Cache Read Pricing
Prompt Cache Write / 1M $0.12 $0.12 Identical Cache Write Pricing
Context Window (Max Output) 131k (16k out) 131k (33k out) Equal Context Window
Avg TTFT Response Latency 115ms 145ms Gemma 4 31B IT (30ms faster)
Generation Speed (Throughput) 155 tok/s 165 tok/s Llama 3.3 70B Instruct (+10 tok/s faster)
SWE-bench Verified (Coding) 59.2% 42.5% Gemma 4 31B IT (+16.7% lead)
GPQA Diamond (PhD STEM) 71.2% 55.6% Gemma 4 31B IT (+15.6% lead)
MMLU-Pro (Multi-Discipline) 82.8% 76.8% Gemma 4 31B IT (+6.0% lead)
MATH-500 (Quantitative Logic) 91.5% 77% Gemma 4 31B IT (+14.5% lead)
Inference Value Score (IVR) 80.3 / 100 74.6 / 100 Gemma 4 31B IT (+5.7 pts)

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

Gemma 4 31B IT $3.68

$0.12/1M in · $0.36/1M out

Prompt Cache: $0.030/1M read · $0.12/1M write

Llama 3.3 70B Instruct $3.38

$0.12/1M in · $0.30/1M out

Prompt Cache: $0.030/1M read · $0.12/1M write

Projected Monthly Cost Reduction
$0.30 / mo
(8.2% lower cost with Llama 3.3 70B Instruct)
Open Full Matchup Analysis →
A

When to Choose Gemma 4 31B IT

Choose Gemma 4 31B IT (Google) for self-hosted VPC inference, fine-tuned domain agents, sovereign healthcare/finance workloads, and low-latency local code generation — offering a 131k context window, 115ms TTFT, and $0.12/1M input pricing ($0.030/1M cached reads).

B

When to Choose Llama 3.3 70B Instruct

Choose Llama 3.3 70B Instruct (Meta) for cost-optimized on-premise deployments, fast text transformation, structured entity extraction, and enterprise dialogue pipelines — offering a 131k context window, 145ms TTFT, and $0.12/1M input pricing ($0.030/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Gemma 4 31B IT or Llama 3.3 70B Instruct?

Both Gemma 4 31B IT and Llama 3.3 70B Instruct share identical input pricing at $0.12/1M tokens.

Which model has lower TTFT latency and higher tok/s throughput: Gemma 4 31B IT or Llama 3.3 70B Instruct?

Gemma 4 31B IT delivers faster first-token latency at 115ms TTFT (155 tok/s throughput) compared to 145ms TTFT (165 tok/s) for Llama 3.3 70B Instruct.

How do Gemma 4 31B IT and Llama 3.3 70B Instruct compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Gemma 4 31B IT scores 59.2% versus 42.5% for Llama 3.3 70B Instruct. On GPQA Diamond graduate-level STEM reasoning, Gemma 4 31B IT scores 71.2% versus 55.6% for Llama 3.3 70B Instruct (and 91.5% vs 77% on MATH-500).

When should you choose Gemma 4 31B IT?

Choose Gemma 4 31B IT (Google) for self-hosted VPC inference, fine-tuned domain agents, sovereign healthcare/finance workloads, and low-latency local code generation — offering a 131k context window, 115ms TTFT, and $0.12/1M input pricing ($0.030/1M cached reads).

When should you choose Llama 3.3 70B Instruct?

Choose Llama 3.3 70B Instruct (Meta) for cost-optimized on-premise deployments, fast text transformation, structured entity extraction, and enterprise dialogue pipelines — offering a 131k context window, 145ms TTFT, and $0.12/1M input pricing ($0.030/1M cached reads).

Explore High-Priority Related Model Matchups