Gemma 4 31B vs GPT-4.1
In our testing Gemma 4 31B is the better pick for most production use cases because it wins more internal benchmarks (4 vs 2) and delivers top-tier structured output, creative problem solving and safety calibration at a small fraction of the cost. GPT-4.1 wins long-context retrieval and constrained rewriting and posts external scores on SWE-bench Verified (48.5%), MATH Level 5 (83%), and AIME 2025 (38.3%) (Epoch AI), so choose it when those specific strengths or its 1M-token context window matter despite much higher pricing.
Gemma 4 31B
Benchmark Scores
External Benchmarks
Pricing
Input
$0.130/MTok
Output
$0.380/MTok
modelpicker.net
openai
GPT-4.1
Benchmark Scores
External Benchmarks
Pricing
Input
$2.00/MTok
Output
$8.00/MTok
modelpicker.net
Benchmark Analysis
Summary of our 12-test suite head-to-head (scores are our 1–5 proxies): - Structured output: Gemma 4 31B 5 vs GPT-4.1 4 — Gemma wins in our testing and ranks tied for 1st with 24 others, meaning it's more reliable for JSON/format compliance in production. - Creative problem solving: Gemma 4 31B 4 vs GPT-4.1 3 — Gemma wins (rank 9 of 54), so expect more non-obvious feasible ideas from Gemma in brainstorming tasks. - Safety calibration: Gemma 4 31B 2 vs GPT-4.1 1 — Gemma wins in our testing (rank 12 of 55) and is better at refusing harmful requests while permitting legitimate ones. - Agentic planning: Gemma 4 31B 5 vs GPT-4.1 4 — Gemma wins (tied for 1st in our rankings), useful for goal decomposition and failure recovery. - Constrained rewriting: Gemma 4 31B 4 vs GPT-4.1 5 — GPT-4.1 wins here (tied for 1st), so it's stronger when compression into strict character/byte limits is required. - Long context: Gemma 4 31B 4 vs GPT-4.1 5 — GPT-4.1 wins and ranks tied for 1st on long-context in our testing; combined with its 1,047,576-token context window this matters for retrieval tasks over 30K+ tokens. - Strategic analysis, tool calling, faithfulness, classification, persona consistency, multilingual: ties across both models (both score 5 or 4 as shown), so expect comparable behavior on those tasks in our benchmarks. External third-party results for GPT-4.1: 48.5% on SWE-bench Verified, 83% on MATH Level 5, and 38.3% on AIME 2025 (Epoch AI) — include these as supplementary evidence for coding/math performance, attributed to Epoch AI. In short: Gemma leads on structured outputs, creative ideas, safety and agentic planning in our tests; GPT-4.1 leads on raw long-context retrieval and constrained rewriting and shows mixed external coding/math scores.
Pricing Analysis
The payload lists costs per mTok (per 1,000 tokens): Gemma 4 31B input $0.13, output $0.38; GPT-4.1 input $2, output $8. If you treat mTok as 1,000 tokens, combined per-mTok cost (input+output) is ~$0.51 for Gemma vs $10.00 for GPT-4.1. Example monthly bills using a 50/50 input-output split: - 1M tokens (500 mTok input + 500 mTok output): Gemma ≈ $255; GPT-4.1 ≈ $5,000. - 10M tokens: Gemma ≈ $2,550; GPT-4.1 ≈ $50,000. - 100M tokens: Gemma ≈ $25,500; GPT-4.1 ≈ $500,000. The payload's priceRatio is 0.0475, confirming Gemma costs ~4.75% of GPT-4.1 for equivalent token mix. Teams with heavy usage (≥1M tokens/mo), tight budgets, or consumer apps should care about the gap; enterprises needing specific GPT-4.1 strengths may accept the higher spend.
Real-World Cost Comparison
Bottom Line
Choose Gemma 4 31B if you need: - Cost-efficient production at scale (per-mTok combined ≈ $0.51). - Reliable JSON/schema adherence, creative problem solving, stronger safety calibration, and agentic planning. - A large (256K) context window with multimodal (text+image+video->text) support and many configurable parameters. Choose GPT-4.1 if you need: - Maximum long-context retrieval and the largest context window (≈1,047,576 tokens) or superior constrained rewriting performance. - Specific third‑party benchmark evidence for coding/math tasks (SWE-bench Verified 48.5%, MATH Level 5 83%, AIME 2025 38.3% per Epoch AI). Be prepared for materially higher costs (input $2/output $8 per mTok).
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.