GPT-5 Mini vs Ministral 3 8B 2512
GPT-5 Mini is the better pick for accuracy-sensitive tasks — it wins 8 of 12 benchmarks in our testing, including structured output, long-context, and faithfulness. Ministral 3 8B 2512 is the lower-cost alternative and beats GPT-5 Mini on tool-calling and constrained rewriting; choose it when budget or tool-selection accuracy matters given GPT-5 Mini’s much higher output cost ($2.00 vs $0.15/mTok).
openai
GPT-5 Mini
Benchmark Scores
External Benchmarks
Pricing
Input
$0.250/MTok
Output
$2.00/MTok
modelpicker.net
mistral
Ministral 3 8B 2512
Benchmark Scores
External Benchmarks
Pricing
Input
$0.150/MTok
Output
$0.150/MTok
modelpicker.net
Benchmark Analysis
Summary: In our 12-test suite GPT-5 Mini wins 8 categories, Ministral 3 8B 2512 wins 2, and 2 are ties (see win/loss data). Detailed walk-through (scores are our internal 1–5 scale unless noted):
- Structured output: GPT-5 Mini 5 vs Ministral 4 — GPT-5 Mini tied for 1st ("tied for 1st with 24 other models out of 54 tested"), meaning it’s among the best at JSON/schema compliance in our tests. This matters for APIs and data pipelines that require strict format adherence.
- Strategic analysis: GPT-5 Mini 5 vs Ministral 3 — GPT-5 Mini is tied for 1st ("tied for 1st with 25 other models out of 54 tested"), showing stronger nuanced tradeoff reasoning (useful for pricing, planning, finance).
- Creative problem solving: GPT-5 Mini 4 vs Ministral 3 — GPT-5 Mini ranks 9 of 54 (tied), indicating better non-obvious idea generation in our tasks.
- Faithfulness: GPT-5 Mini 5 vs Ministral 4 — GPT-5 Mini tied for 1st ("tied for 1st with 32 other models out of 55 tested"), so it better sticks to source material in our evaluations.
- Long context: GPT-5 Mini 5 vs Ministral 4 — GPT-5 Mini tied for 1st ("tied for 1st with 36 other models out of 55 tested"), which matters for 30K+ token retrieval and multi-document synthesis.
- Safety calibration: GPT-5 Mini 3 vs Ministral 1 — GPT-5 Mini ranks 10 of 55 ("rank 10 of 55 (2 models share this score)"), while Ministral ranks 32 of 55; GPT-5 Mini more reliably refuses harmful prompts in our tests.
- Agentic planning: GPT-5 Mini 4 vs Ministral 3 — GPT-5 Mini ranks 16 of 54 vs Ministral 42 of 54, so GPT-5 Mini better decomposes goals and recovery planning in our scenarios.
- Multilingual: GPT-5 Mini 5 vs Ministral 4 — GPT-5 Mini tied for 1st ("tied for 1st with 34 other models out of 55 tested"), giving it a clear edge when the product must support many languages.
- Constrained rewriting: GPT-5 Mini 4 vs Ministral 5 — Ministral 3 8B 2512 ties for 1st ("tied for 1st with 4 other models out of 53 tested") and wins here; it’s stronger when output must be compressed into strict character limits.
- Tool calling: GPT-5 Mini 3 vs Ministral 4 — Ministral wins and ranks 18 of 54 ("rank 18 of 54 (29 models share this score)"), while GPT-5 Mini ranks 47 of 54; Ministral is preferable when function selection and argument accuracy are primary.
- Classification and Persona consistency: ties at the same scores — classification 4 (both tied for 1st), persona consistency 5 (both tied for 1st), so both models are comparable for routing and character/agreement tasks. External (third-party) benchmarks: Beyond our internal tests, GPT-5 Mini scores 64.7% on SWE-bench Verified, 97.8% on MATH Level 5, and 86.7% on AIME 2025 (these external scores are from Epoch AI). Ministral 3 8B 2512 has no external scores in the payload to reference. These external results supplement our finding that GPT-5 Mini is stronger on coding/math-hard tasks, while Ministral’s wins on constrained rewriting and tool calling reflect different strengths.
Pricing Analysis
Per the payload pricing, GPT-5 Mini charges $0.25/mTok input and $2.00/mTok output; Ministral 3 8B 2512 charges $0.15/mTok input and $0.15/mTok output. That output gap (2.00 / 0.15 = 13.33x) drives the difference at scale. Example totals for 1M tokens (1,000 mTok): GPT-5 Mini = $250 input + $2,000 output = $2,250; Ministral = $150 input + $150 output = $300. For 10M tokens: GPT-5 Mini = $22,500 vs Ministral = $3,000. For 100M tokens: GPT-5 Mini = $225,000 vs Ministral = $30,000. Who should care: high-volume services (chat fleets, SaaS features, high-throughput APIs) where tens of millions of tokens/month are typical will see substantial monthly savings with Ministral; teams prioritizing top-tier structured output, long-context reasoning, or math performance may justify GPT-5 Mini’s higher cost for fewer users or premium features.
Real-World Cost Comparison
Bottom Line
Choose GPT-5 Mini if you need best-in-class structured output, long-context reasoning, strong faithfulness, multilingual quality, or math/coding competence (it wins 8 of 12 internal benchmarks and posts external scores of 64.7% SWE-bench Verified, 97.8% MATH Level 5, 86.7% AIME 2025 per Epoch AI). Accept the higher cost ($2.00/mTok output) for those capabilities. Choose Ministral 3 8B 2512 if you need a much lower-cost model for high-volume use or for workflows that prioritize tool calling and tight constrained rewriting (it wins those two categories and charges $0.15/mTok output), or when budget drives deployment across millions of monthly tokens.
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.