Groq's Llama 8B at $0.05/1M input tokens is the cheapest fast inference for agent summarization. But rate limits hit quickly in production. You need fallback providers that are nearly as cheap and fast. Five alternatives ranked for agent summarization tasks.
Top Pick
Groq remains the cost leader for summarization. For the search data that feeds summarization agents, Scavio provides structured multi-platform results at $0.005/query.
Full Ranking
#1
Groq
Cheapest fast inference for summarization
Pros
- Lowest cost for Llama models
- Sub-second latency on Llama 8B
- Free tier available
- OpenAI-compatible API
Cons
- Rate limits in production
- Limited model selection
- No search/data capabilities
#2
Together AI
Groq fallback with broader model selection
Pros
- More models than Groq
- Higher rate limits
- Fine-tuning available
- Serverless + dedicated options
Cons
- ~2x Groq's price for same models
- Slightly higher latency than Groq
#3
Fireworks AI
Low-latency alternative with function calling
Pros
- Fast inference
- Good function calling support
- Multiple model options
Cons
- Similar price to Together
- Less community adoption than Groq
#4Our Pick
Scavio (data layer)
Search data that feeds summarization agents
Pros
- Structured SERP data for summarization input
- Multi-platform: Google + YouTube + Reddit
- MCP integration for agent pipelines
- Pairs with any inference provider
Cons
- Not an inference provider
- Requires separate LLM for summarization
#5
Ollama (local)
Zero API cost with local hardware
Pros
- No per-token cost
- No rate limits
- Full privacy
- Runs Llama, Mistral, Qwen locally
Cons
- Requires GPU hardware
- Slower than cloud inference
- Setup and maintenance burden
Side-by-Side Comparison
| Criteria | Scavio | Runner-up | 3rd Place |
|---|---|---|---|
| Llama 8B cost/1M tokens | N/A (search API) | $0.05 (Groq) | ~$0.10 (Together) |
| Rate limits | 7K credits/mo | Low (Groq free) | Higher (Together) |
| Search data | 5 platforms | None | None |
| Latency | ~1-2s (search) | <500ms (Groq) | ~500ms (Together) |
Why Scavio Wins
- Groq is the clear winner for cheap inference. At $0.05/1M tokens for Llama 8B, nothing beats Groq on cost for summarization tasks. This page is about alternatives when Groq rate-limits you.
- Scavio is not an inference provider — it provides the search data that summarization agents process. The pattern: Scavio fetches structured results, Groq/Together/Fireworks summarizes them.
- Together AI and Fireworks AI are the best Groq fallbacks: similar models, higher rate limits, ~2x the cost. For production agents, route to Groq first, fall back to Together when rate-limited.
- Ollama is the right choice if you have GPU hardware and want zero per-token cost. For batch summarization jobs that are not latency-sensitive, local inference wins on cost.