Model Selection & Cost Guide
CiniterFlow supports 30+ AI models from 15+ providers. This guide helps you pick the right model for each task and keep your costs under control.
The Golden Rule
Use the cheapest model that gets the job done. Don't use GPT-4o for a simple routing decision that GPT-4o-mini handles perfectly. Don't use GPT-4o-mini for a complex research synthesis that needs GPT-4o's reasoning.
Quick Decision Matrix
Not sure which model to use? Start here:
| Task | Recommended Model | Why |
|---|---|---|
| Routing / Classification | GPT-4o-mini, Gemini Flash | Fast, cheap, accurate for simple decisions |
| Customer support chat | GPT-4o-mini, Claude 3.5 Sonnet | Good balance of quality and cost |
| Complex reasoning | GPT-4o, Claude 3.5 Sonnet | Better at multi-step logic |
| Long document analysis | Gemini 1.5 Pro | 1M+ token context window |
| Code generation | Claude 3.5 Sonnet, GPT-4o | Best at writing and reviewing code |
| Creative writing | Claude 3.5 Sonnet, GPT-4o | Most natural, engaging output |
| Data extraction / JSON | GPT-4o-mini, GPT-4o | Most reliable structured output |
| Research synthesis | Gemini 1.5 Pro | Handles massive context from multiple sources |
| Fast inference needed | Groq (Llama), Gemini Flash | Sub-second response times |
| Budget-conscious | Deepseek V3, GPT-4o-mini | Lowest cost per token |
| Supervisor/Router agent | GPT-4o-mini | Only makes decisions, doesn't need power |
| Worker/Specialist agent | GPT-4o, Claude 3.5 Sonnet | Needs quality for the actual work |
Provider Comparison
OpenAI
| Model | Best For | Speed | Quality | Context | Approximate Cost (per 1M tokens) |
|---|---|---|---|---|---|
| GPT-4o | Complex tasks, reasoning | Medium | ⭐⭐⭐⭐⭐ | 128K | $2.50 input / $10 output |
| GPT-4o-mini | Most tasks, routing, simple chat | Fast | ⭐⭐⭐⭐ | 128K | $0.15 input / $0.60 output |
When to use OpenAI:
- Most reliable structured output (JSON mode)
- Best all-rounder for general tasks
- Largest ecosystem and community support
- GPT-4o-mini is the best "default" model for most use cases
Anthropic (Claude)
| Model | Best For | Speed | Quality | Context | Approximate Cost (per 1M tokens) |
|---|---|---|---|---|---|
| Claude 3.5 Sonnet | Code, writing, instruction-following | Medium | ⭐⭐⭐⭐⭐ | 200K | $3 input / $15 output |
| Claude 3 Haiku | Fast, cheap tasks | Very Fast | ⭐⭐⭐ | 200K | $0.25 input / $1.25 output |
When to use Anthropic:
- Best at following complex, nuanced instructions
- Excellent for code generation and review
- Most natural-sounding writing
- Tip: Put task-specific instructions in the User message, not System message
Google (Gemini)
| Model | Best For | Speed | Quality | Context | Approximate Cost (per 1M tokens) |
|---|---|---|---|---|---|
| Gemini 1.5 Pro | Long documents, research | Medium | ⭐⭐⭐⭐⭐ | 2M | $1.25 input / $5 output |
| Gemini 1.5 Flash | Fast, cheap tasks | Very Fast | ⭐⭐⭐⭐ | 1M | $0.075 input / $0.30 output |
When to use Google:
- Unmatched context window (up to 2M tokens)
- Best for synthesizing large amounts of research
- Gemini Flash is extremely cost-effective
- Generous free tier for getting started
Deepseek
| Model | Best For | Speed | Quality | Context | Approximate Cost (per 1M tokens) |
|---|---|---|---|---|---|
| Deepseek V3 | General tasks on a budget | Medium | ⭐⭐⭐⭐ | 64K | $0.27 input / $1.10 output |
| Deepseek R1 | Complex reasoning | Slow | ⭐⭐⭐⭐⭐ | 64K | $0.55 input / $2.19 output |
When to use Deepseek:
- Best cost-to-quality ratio
- R1 has exceptional reasoning capabilities
- Great for budget-conscious production deployments
Groq
| Model | Best For | Speed | Quality | Context | Approximate Cost (per 1M tokens) |
|---|---|---|---|---|---|
| Llama 3.1 70B | Fast inference | Extremely Fast | ⭐⭐⭐⭐ | 128K | $0.59 input / $0.79 output |
| Mixtral 8x7B | Fast, cheap tasks | Extremely Fast | ⭐⭐⭐ | 32K | $0.24 input / $0.24 output |
When to use Groq:
- When speed is the top priority
- Sub-second response times
- Good for real-time applications
Other Notable Providers
| Provider | Model | Best For | Notes |
|---|---|---|---|
| xAI | Grok | General tasks | Good all-rounder, competitive pricing |
| Fireworks | Various | Fast inference | Optimized for speed |
| Together AI | Open-source models | Budget tasks | Access to many open-source models |
| Perplexity | pplx-online | Web-connected answers | Built-in web search |
| AWS Bedrock | Various | Enterprise | AWS-native, compliance-friendly |
| Azure OpenAI | GPT models | Enterprise | Azure-native, compliance-friendly |
Cost Optimization Strategies
Strategy 1: Tiered Model Usage
Use different models for different parts of your flow:
Start → GPT-4o-mini (route the question) ← $0.15/M tokens
→ GPT-4o-mini (generate search query) ← $0.15/M tokens
→ [Retriever searches documents]
→ GPT-4o (generate final answer) ← $2.50/M tokens
The expensive model only runs once (for the final answer), while cheap models handle routing and query generation.
Strategy 2: Reduce Token Usage
- Shorter prompts: Every token in your system prompt is sent with every message. Cut unnecessary words
- Limit conversation history: Use Buffer Window Memory (last 5-10 messages) instead of full Buffer Memory
- Smaller chunks: In RAG, retrieve fewer but more relevant chunks (lower Top K)
- Structured output: Use JSON Structured Output to get concise, parseable responses instead of verbose text
Strategy 3: Cache and Reuse
- Document Store: Upsert once, query many times (don't re-process documents)
- Variables: Store frequently used values instead of regenerating them
- Flow State: Pass data between nodes via state instead of re-querying
Strategy 4: Right-Size Your Context
| Scenario | Context Needed | Model Choice |
|---|---|---|
| Simple Q&A | Small (< 4K tokens) | GPT-4o-mini |
| RAG with 5 chunks | Medium (< 16K tokens) | GPT-4o-mini |
| Long document analysis | Large (> 100K tokens) | Gemini 1.5 Pro |
| Multi-agent synthesis | Very Large (> 500K tokens) | Gemini 1.5 Pro |
Don't pay for a 128K context window when your actual usage is 4K tokens — but also don't try to squeeze 100K tokens into a model that struggles with long context.
Strategy 5: Monitor and Adjust
Use CiniterFlow's analytics integrations (Langfuse, LangWatch, etc.) to track:
- Token usage per flow: Which flows consume the most tokens?
- Cost per conversation: How much does each user interaction cost?
- Latency: Are you paying for speed you don't need?
- Error rates: Are cheaper models failing too often, causing expensive retries?
Cost Estimation Examples
Here's what typical use cases cost per 1,000 conversations (using GPT-4o-mini for most tasks):
| Use Case | Avg Tokens/Conversation | Cost per 1K Conversations |
|---|---|---|
| Simple FAQ bot | ~2,000 | ~$0.45 |
| Customer support (with RAG) | ~5,000 | ~$1.50 |
| Multi-agent routing system | ~10,000 | ~$3.00 |
| Deep research agent | ~100,000 | ~$30.00 |
These are rough estimates using GPT-4o-mini pricing. Using GPT-4o would be approximately 15-20x more expensive.
Recommendations by Budget
"I want to spend as little as possible"
- Primary: GPT-4o-mini or Gemini Flash for everything
- Fallback: Deepseek V3 for tasks that need more power
- Estimated cost: $5-20/month for moderate usage
"I want the best quality"
- Routing: GPT-4o-mini
- Main tasks: GPT-4o or Claude 3.5 Sonnet
- Long context: Gemini 1.5 Pro
- Estimated cost: $50-200/month for moderate usage
"I need enterprise-grade reliability"
- Primary: Azure OpenAI or AWS Bedrock (for compliance)
- Fallback: Multiple providers for redundancy
- Monitoring: Langfuse or LangWatch for observability
- Estimated cost: Varies by volume
Setting Up Multiple Providers
We strongly recommend configuring at least 2-3 providers in CiniterFlow:
- Go to Credentials in the sidebar
- Add credentials for your primary provider (e.g., OpenAI)
- Add credentials for a secondary provider (e.g., Google)
- Add credentials for a budget option (e.g., Deepseek or Groq)
This gives you flexibility to:
- Use the right model for each task
- Fall back to another provider if one has an outage
- A/B test different models to find the best quality-to-cost ratio
tip
Pricing changes frequently. Check each provider's pricing page for the latest rates before making decisions.