💰 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 o1 78% GPQA · 96.4% MATH-500

Which model is better: Gemma 4 31B IT or o1?

Gemma 4 31B IT is 99.2% cheaper for input tokens ($0.12 vs. $15.00 per 1M tokens) and $0.36 vs. $60.00 for output tokens (125.0x cost advantage). In terms of operational performance, Gemma 4 31B IT delivers lower response latency at 115ms TTFT (2485ms faster than o1) with 155 vs. 48 tok/s throughput. Gemma 4 31B IT leads coding evaluations at 59.2% SWE-bench Verified vs. 48.9% for o1 and 71.2% vs. 78.0% 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 o1 Net Delta / Advantage
Input Cost / 1M Tokens $0.12 $15.00 Gemma 4 31B IT is 125.0x cheaper
Output Cost / 1M Tokens $0.36 $60.00 Gemma 4 31B IT (99.4% lower)
Prompt Cache Read / 1M $0.030 $7.500 Gemma 4 31B IT is 250.0x cheaper
Prompt Cache Write / 1M $0.12 $15.00 Gemma 4 31B IT is 125.0x cheaper
Context Window (Max Output) 131k (16k out) 205k (100k out) o1 (1.6x larger context)
Avg TTFT Response Latency 115ms 2600ms Gemma 4 31B IT (2485ms faster)
Generation Speed (Throughput) 155 tok/s 48 tok/s Gemma 4 31B IT (+107 tok/s faster)
SWE-bench Verified (Coding) 59.2% 48.9% Gemma 4 31B IT (+10.3% lead)
GPQA Diamond (PhD STEM) 71.2% 78% o1 (+6.8% lead)
MMLU-Pro (Multi-Discipline) 82.8% 83.3% o1 (+0.5% lead)
MATH-500 (Quantitative Logic) 91.5% 96.4% o1 (+4.9% lead)
Inference Value Score (IVR) 80.3 / 100 37.2 / 100 Gemma 4 31B IT (+43.1 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

o1 $581.25

$15.00/1M in · $60.00/1M out

Prompt Cache: $7.500/1M read · $15.00/1M write

Projected Monthly Cost Reduction
$577.58 / mo
(99.4% lower cost with Gemma 4 31B IT)
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 o1

Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Gemma 4 31B IT or o1?

Gemma 4 31B IT is cheaper at $0.12/1M input tokens ($0.36/1M output) compared to $15.00/1M input ($60.00/1M output) for o1.

Which model has lower TTFT latency and higher tok/s throughput: Gemma 4 31B IT or o1?

Gemma 4 31B IT delivers faster first-token latency at 115ms TTFT (155 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.

How do Gemma 4 31B IT and o1 compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Gemma 4 31B IT scores 59.2% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, Gemma 4 31B IT scores 71.2% versus 78% for o1 (and 91.5% vs 96.4% 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 o1?

Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).

Explore High-Priority Related Model Matchups