Best Models for Business

Open-source models that deliver real value for common business tasks — and run on affordable hardware.

Quick Reference

Model	Size	VRAM (4-bit)	VRAM (8-bit)	Est. tok/s (V100)	Best For
Llama 3.2 3B	3B	2.5 GB	4 GB	80-100	Simple tasks, chatbots, classification
Mistral 7B	7B	5 GB	8 GB	50-70	General purpose, balanced performance
Llama 3.1 8B	8B	6 GB	10 GB	45-60	General purpose, excellent instruction following
Gemma 2 9B	9B	7 GB	11 GB	40-55	Enterprise tasks, structured output
Qwen 2.5 14B	14B	10 GB	16 GB	25-35	Coding, reasoning, multilingual
Mistral NeMo 12B	12B	9 GB	14 GB	30-40	Long context, document analysis
Qwen 2.5 Coder 7B	7B	5 GB	8 GB	50-70	Code generation, debugging
Qwen 2.5 Coder 32B	32B	22 GB	36 GB	12-18	Professional coding, complex reasoning
Mixtral 8x7B	47B*	24 GB	45 GB	15-25	High-quality output, MoE efficiency
Llama 3.3 70B	70B	40 GB	75 GB	5-8	Complex reasoning, premium quality

*Mixtral uses Mixture of Experts: 47B total params, ~13B active per token

Business Use Cases

1. Customer Support & Chatbots

Recommended: Mistral 7B, Llama 3.1 8B, Gemma 2 9B

Requirement	Minimum	Recommended
Response quality	Good	Excellent
Speed needed	30+ tok/s	50+ tok/s
VRAM	8 GB	16 GB

What it does:

Answer FAQs
Route tickets
Draft responses
Handle common queries 24/7

2. Document Summarization

Recommended: Mistral NeMo 12B, Llama 3.1 8B, Gemma 2 9B

Document Size	Model	VRAM
Short (<4K tokens)	Mistral 7B	8 GB
Medium (4K-16K)	Mistral NeMo 12B	16 GB
Long (16K-128K)	Llama 3.1 8B	16 GB

What it does:

Summarize reports, emails, contracts
Extract key points from meetings
Create executive summaries

3. Translation & Localization

Recommended: Qwen 2.5 14B, Llama 3.1 8B

Languages	Model	Notes
EN/DE/FR/ES	Llama 3.1 8B	Good for European languages
30+ languages	Qwen 2.5 14B	Excellent multilingual support
Technical docs	Qwen 2.5 14B	Better at preserving terminology

What it does:

Translate documents, emails, websites
Localize content for markets
Real-time translation assistance

4. Code Generation & Review

Recommended: Qwen 2.5 Coder 7B, Qwen 2.5 Coder 32B

Task	Model	VRAM	Quality
Simple functions	Qwen 2.5 Coder 7B	8 GB	⭐⭐⭐⭐
Bug fixes	Qwen 2.5 Coder 7B	8 GB	⭐⭐⭐⭐
Code review	Qwen 2.5 Coder 14B	12 GB	⭐⭐⭐⭐⭐
Complex refactoring	Qwen 2.5 Coder 32B	24 GB	⭐⭐⭐⭐⭐
Architecture decisions	Qwen 2.5 Coder 32B	24 GB	⭐⭐⭐⭐⭐

What it does:

Generate code from descriptions
Debug and fix errors
Write tests
Explain code
Refactor legacy code

5. Content Writing & Marketing

Recommended: Llama 3.1 8B, Mistral 7B, Gemma 2 9B

Content Type	Model	Why
Social media posts	Mistral 7B	Fast, creative
Blog articles	Llama 3.1 8B	Better structure
Email campaigns	Gemma 2 9B	Professional tone
Product descriptions	Llama 3.1 8B	Consistent quality

What it does:

Draft marketing copy
Write blog posts
Create social media content
Generate email templates

6. Data Analysis & Reporting

Recommended: Llama 3.1 8B, Qwen 2.5 14B

Task	Model	Speed	Quality
SQL generation	Qwen 2.5 Coder 7B	Fast	⭐⭐⭐⭐
Data interpretation	Qwen 2.5 14B	Medium	⭐⭐⭐⭐⭐
Report writing	Llama 3.1 8B	Fast	⭐⭐⭐⭐
Chart descriptions	Gemma 2 9B	Fast	⭐⭐⭐⭐

What it does:

Generate SQL queries
Interpret data patterns
Write analysis reports
Create data summaries

Performance Requirements

Tokens/Second Guidelines

Use Case	Minimum	Comfortable	Excellent
Chatbot	20 tok/s	40 tok/s	60+ tok/s
Document processing	15 tok/s	30 tok/s	50+ tok/s
Batch processing	10 tok/s	20 tok/s	40+ tok/s
Real-time assistance	30 tok/s	50 tok/s	80+ tok/s

Human reading speed: ~250 words/minute = ~4 words/second ≈ 5-6 tok/s

Latency vs Throughput

Latency (TTFT): Time to first token — important for chatbots
Throughput: Total tokens/second — important for batch processing

Hardware	7B model tok/s	14B model tok/s	70B model tok/s
Tesla P100	35-50	15-25	3-6
Tesla V100	50-70	25-40	5-10
Tesla T4	30-45	12-20	3-5
2x V100	90-120	45-70	10-18

Model Selection by Budget

Under €2,000 (2x P100, 32GB VRAM total)

✅ Mistral 7B (fast, reliable)
✅ Llama 3.1 8B (great instruction following)
✅ Qwen 2.5 Coder 7B (coding)
✅ Gemma 2 9B (enterprise tasks)
⚠️ Qwen 2.5 14B (tight fit, single GPU)
❌ Mixtral, 70B models

€3,000-5,000 (2x V100 16GB or 2x T4, 32GB VRAM)

✅ All models from above (faster)
✅ Qwen 2.5 14B (comfortable)
✅ Qwen 2.5 Coder 32B (tight fit)
⚠️ Mixtral 8x7B (quantized, slow)
❌ 70B models

€6,000-8,000 (2x V100 32GB, 64GB VRAM)

✅ All smaller models (very fast)
✅ Qwen 2.5 Coder 32B (comfortable)
✅ Mixtral 8x7B (good speed)
⚠️ Llama 3.3 70B (4-bit, usable)

Our Recommendations

Best All-Rounder

Llama 3.1 8B — Excellent instruction following, good at most tasks, fits on any GPU.

Best for Coding

Qwen 2.5 Coder 32B — Matches GPT-4 on coding benchmarks. Needs 24GB+ VRAM.

Best for Multilingual

Qwen 2.5 14B — Supports 30+ languages, great translation quality.

Best for Documents

Mistral NeMo 12B — 128K context window, excellent for long documents.

Best Budget Option

Mistral 7B — Punches above its weight, very fast, runs on anything.

Getting Started

All models are available through:

Ollama: ollama run llama3.1:8b
vLLM: Production-grade serving
llama.cpp: Lightweight, CPU+GPU hybrid

We pre-install and configure these on all our servers.

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