Gemma 4 31B vs GPT-4o
In our testing Gemma 4 31B is the better all-around pick: it wins 9 of 12 internal benchmarks (tool calling, structured output, strategic analysis) while costing far less. GPT-4o does not win any of our internal tests and is ~25x more expensive, but it offers file->text input and OpenAI ecosystem compatibility for teams willing to pay a premium.
Gemma 4 31B
Benchmark Scores
External Benchmarks
Pricing
Input
$0.130/MTok
Output
$0.380/MTok
modelpicker.net
openai
GPT-4o
Benchmark Scores
External Benchmarks
Pricing
Input
$2.50/MTok
Output
$10.00/MTok
modelpicker.net
Benchmark Analysis
Summary of our 12-test suite (scores on a 1–5 scale): Gemma 4 31B wins 9 tests, GPT-4o wins 0, and they tie on 3. Detailed walk-through: - Structured output: Gemma 5 vs GPT-4o 4. In our testing Gemma is tied for 1st of 54 on JSON/schema compliance, while GPT-4o ranks 26 of 54 — choose Gemma when exact format adherence matters. - Strategic analysis: Gemma 5 vs GPT-4o 2. Gemma is tied for 1st (nuanced tradeoff reasoning), GPT-4o ranks 44/54 — Gemma handles numeric tradeoffs and multi-step reasoning better in our tests. - Tool calling: Gemma 5 vs GPT-4o 4. Gemma tied for 1st of 54 for function selection and argument accuracy; GPT-4o ranks 18/54 — Gemma is less likely to pick incorrect tools or bad args in our tool-calling scenarios. - Agentic planning: Gemma 5 vs GPT-4o 4. Gemma tied for 1st (goal decomposition, failure recovery); GPT-4o is mid-ranked. - Faithfulness: Gemma 5 vs GPT-4o 4. Gemma tied for 1st (sticks to source material); GPT-4o sits lower in the distribution. - Multilingual & Persona consistency: Gemma 5 vs GPT-4o 4 (multilingual) and both score 5 on persona consistency — these are ties for persona and a clear win for Gemma on multilingual in our tests. - Creative problem solving: Gemma 4 vs GPT-4o 3 — Gemma ranks 9/54 vs GPT-4o 30/54. - Constrained rewriting, classification, safety calibration, long context: Gemma wins constrained rewriting (4 vs 3) and safety calibration (2 vs 1); classification and long context are ties (both models score 4 on long context and tie for classification). External benchmarks: GPT-4o has third-party scores included in the payload — on SWE-bench Verified (Epoch AI) GPT-4o scores 31% (ranked 12 of 12), on MATH Level 5 it scores 53.3% (rank 12 of 14), and on AIME 2025 it scores 6.4% (rank 22 of 23). We report those as Epoch AI results; Gemma has no SWE-bench/MATH/AIME external scores in the payload. Overall implication: Gemma is clearly stronger in structured outputs, tool orchestration, strategic/agentic tasks and multilingual/faithfulness in our internal suite; GPT-4o’s external SWE-bench and math scores in the payload are low relative to peers and do not offset Gemma’s internal wins.
Pricing Analysis
Per the payload, Gemma 4 31B charges $0.13 input + $0.38 output = $0.51 per mTok; GPT-4o charges $2.50 input + $10.00 output = $12.50 per mTok. At a 50/50 input/output token split this yields: 1M tokens (1,000 mTok) = Gemma $510 vs GPT-4o $12,500; 10M = Gemma $5,100 vs GPT-4o $125,000; 100M = Gemma $51,000 vs GPT-4o $1,250,000. PriceRatio in the payload is 0.038 (Gemma cost ≈3.8% of GPT-4o). Teams with high-throughput pipelines, startups, or any cost-sensitive production workloads should prefer Gemma. Organizations that prioritize specific vendor integrations or file->text input and can absorb an order-of-magnitude higher bill may still choose GPT-4o.
Real-World Cost Comparison
Bottom Line
Choose Gemma 4 31B if: you need reliable structured outputs, accurate tool calling, strong strategic reasoning, multilingual fidelity, or are billing-sensitive — Gemma scores 5 on tool calling, structured output, strategic analysis, faithfulness, agentic planning and costs $0.51/mTok in our pricing. Choose GPT-4o if: you require OpenAI platform integration or file->text input workflows present in the payload and you can absorb substantially higher costs (GPT-4o = $12.50/mTok); note that GPT-4o does not win any of our internal benchmarks and posts weak external SWE-bench/MATH/AIME scores in the payload.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.