DeepSeek V3.1 vs Ministral 3 3B 2512

DeepSeek V3.1 is the better pick for the most common high‑value use cases — it wins 6 of 12 benchmarks, notably long‑context and structured output. Ministral 3 3B 2512 beats it on constrained rewriting, tool calling, and classification and is dramatically cheaper on output tokens, so pick it when cost or vision input matters.

deepseek

DeepSeek V3.1

Overall
3.92/5Strong

Benchmark Scores

Faithfulness
5/5
Long Context
5/5
Multilingual
4/5
Tool Calling
3/5
Classification
3/5
Agentic Planning
4/5
Structured Output
5/5
Safety Calibration
1/5
Strategic Analysis
4/5
Persona Consistency
5/5
Constrained Rewriting
3/5
Creative Problem Solving
5/5

External Benchmarks

SWE-bench Verified
N/A
MATH Level 5
N/A
AIME 2025
N/A

Pricing

Input

$0.150/MTok

Output

$0.750/MTok

Context Window33K

modelpicker.net

mistral

Ministral 3 3B 2512

Overall
3.58/5Strong

Benchmark Scores

Faithfulness
5/5
Long Context
4/5
Multilingual
4/5
Tool Calling
4/5
Classification
4/5
Agentic Planning
3/5
Structured Output
4/5
Safety Calibration
1/5
Strategic Analysis
2/5
Persona Consistency
4/5
Constrained Rewriting
5/5
Creative Problem Solving
3/5

External Benchmarks

SWE-bench Verified
N/A
MATH Level 5
N/A
AIME 2025
N/A

Pricing

Input

$0.100/MTok

Output

$0.100/MTok

Context Window131K

modelpicker.net

Benchmark Analysis

Summary: DeepSeek V3.1 wins 6 benchmarks, Ministral 3 3B 2512 wins 3, and 3 are ties (faithfulness, safety_calibration, multilingual). Detailed walk‑through (score A = DeepSeek, B = Ministral; rankings from our suite):

  • Faithfulness: A 5 vs B 5 — tie. Both models are top‑ranked for sticking to source material (DeepSeek and Ministral tied for 1st with many models). For tasks needing literal fidelity, either is acceptable in our tests.

  • Constrained rewriting: A 3 vs B 5 — Ministral wins. Ministral is tied for 1st in constrained rewriting (compression to hard limits), so it’s the better choice for tight character/byte budgets and compression tasks.

  • Safety calibration: A 1 vs B 1 — tie. Both score 1 and rank mid/low (rank 32 of 55), meaning neither reliably balances refusals vs legitimate requests in our safety probe.

  • Tool calling: A 3 vs B 4 — Ministral wins. Ministral ranks 18 of 54 (better relative position) for function selection and argument sequencing; expect fewer tool‑selection mistakes with Ministral on function-calling flows.

  • Structured output: A 5 vs B 4 — DeepSeek wins. DeepSeek is tied for 1st on JSON/schema compliance in our tests, making it stronger where strict format adherence is required (APIs, data extraction).

  • Agentic planning: A 4 vs B 3 — DeepSeek wins. DeepSeek ranks 16 of 54 for goal decomposition and recovery, useful for multi‑step agents and planners.

  • Multilingual: A 4 vs B 4 — tie. Both score equally; neither has a measurable edge in our multilingual tests.

  • Classification: A 3 vs B 4 — Ministral wins. Ministral is tied for 1st in classification (accurate routing/categorization), so prefer it for label assignment and automated routing.

  • Long context: A 5 vs B 4 — DeepSeek wins. Despite DeepSeek’s 32,768 token context window versus Ministral’s 131,072, DeepSeek scored 5 and is tied for 1st in our long‑context retrieval accuracy tests — it performed better on retrieval and reasoning across long inputs in our suite.

  • Persona consistency: A 5 vs B 4 — DeepSeek wins. DeepSeek ties for 1st on maintaining character and resisting injection; use it where consistent persona/roleplay matters.

  • Strategic analysis: A 4 vs B 2 — DeepSeek wins. DeepSeek’s 4 (rank 27 of 54) shows stronger nuanced tradeoff reasoning with numbers — valuable for pricing, risk, and scenario analysis.

  • Creative problem solving: A 5 vs B 3 — DeepSeek wins. DeepSeek ties for 1st on non‑obvious, feasible ideas; it’s better for ideation and synthesis tasks in our tests.

Practical meaning: DeepSeek is the stronger generalist for long documents, structured outputs, planning, and creative/strategic tasks. Ministral is the better value for classification, constrained rewriting, and tool‑calling flows, and it supports text+image->text modality which matters for vision‑enabled tasks.

BenchmarkDeepSeek V3.1Ministral 3 3B 2512
Faithfulness5/55/5
Long Context5/54/5
Multilingual4/54/5
Tool Calling3/54/5
Classification3/54/5
Agentic Planning4/53/5
Structured Output5/54/5
Safety Calibration1/51/5
Strategic Analysis4/52/5
Persona Consistency5/54/5
Constrained Rewriting3/55/5
Creative Problem Solving5/53/5
Summary6 wins3 wins

Pricing Analysis

Costs (per 1,000 tokens): DeepSeek V3.1 charges $0.15 input and $0.75 output; Ministral 3 3B 2512 charges $0.10 input and $0.10 output. Assuming a 50/50 split of input/output tokens: per 1M tokens (1,000 mTok) DeepSeek ≈ $450 (input $75 + output $375) vs Ministral ≈ $100 (input $50 + output $50) — a $350/month gap. At 10M tokens the gap is ~$3,500/month (DeepSeek $4,500 vs Ministral $1,000); at 100M tokens the gap is ~$35,000/month (DeepSeek $45,000 vs Ministral $10,000). The payload gives a priceRatio of 7.5 driven by output pricing. High‑volume deployments, startups on tight budgets, and cost‑sensitive consumer apps should care most about the gap; research or enterprise teams that need DeepSeek’s higher-scoring long‑context and structured outputs may justify the premium.

Real-World Cost Comparison

TaskDeepSeek V3.1Ministral 3 3B 2512
iChat response<$0.001<$0.001
iBlog post$0.0016<$0.001
iDocument batch$0.041$0.0070
iPipeline run$0.405$0.070

Bottom Line

Choose DeepSeek V3.1 if you need the highest‑quality long‑context reasoning, strict schema/JSON outputs, persona consistency, strategic analysis, or creative problem solving in production workflows and can absorb the higher output cost. Choose Ministral 3 3B 2512 if you need a much lower cost per token, classification, constrained rewriting, or stronger tool‑calling behavior — and if you want text+image->text capability at a fraction of the price.

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.

Frequently Asked Questions