Fireworks AI vs Sambanova
Fireworks AI scores higher on the AgentReady, 59/100 against 48/100. They differ on 13 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.
What each one is
Fireworks AI. Fireworks AI is the fastest platform for building with open source AI models, providing production-ready inference and fine-tuning with best-in-class speed, cost and quality.
Sambanova. SambaNova is an AI infrastructure company pushing the AI frontier with premium inference, maximizing dataflow efficiency with high speed and sustained throughput for running the largest models.
Where Fireworks AI is ahead
Fireworks AI passes public docs discoverable and llms-full.txt / full agent docs, and Sambanova does not. That is discover, whether an agent can find the product at all without being told it exists.
It also holds understand: pricing understandable and limits / constraints documented. Sambanova misses those.
And on adopt, self-service signup, agent-compatible signup flow, free trial or free allowance, fast time to first request and cli available. Sambanova misses those.
Finally, on operate, structured, predictable output. Sambanova misses it.
Where Sambanova is ahead
Sambanova passes mcp discoverable, and Fireworks AI does not. That is discover, whether an agent can find the product at all without being told it exists.
It also holds understand: structured api reference. Fireworks AI misses it.
And on adopt, mcp integration available. Fireworks AI misses it.
What neither does
Both fail openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, no mandatory sales call, programmatic credential creation, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. If your agent needs any of those, you will be building it yourself either way.
Score, pillar by pillar
The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.
Discover. Fireworks AI leads 87 to 80. Fireworks AI misses mcp discoverable; Sambanova misses public docs discoverable, llms-full.txt / full agent docs.
Understand. Both sit at 38/100 here. Fireworks AI misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented; Sambanova misses openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.
Adopt is whether an agent can get a key and make its first successful call without a human in the loop. Fireworks AI leads 65 to 40. Fireworks AI misses no mandatory sales call, programmatic credential creation, mcp integration available; Sambanova misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, cli available.
Operate. Fireworks AI leads 47 to 35. Fireworks AI misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified; Sambanova misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.
Pricing
Fireworks AI does not publish a machine-readable starting price and has a free tier. Sambanova does not publish one.
| Fireworks AI plans | Sambanova plans |
|---|---|
| Serverless Inference Pay per token | - |
| Embeddings - up to 150M $0.008 / 1M input tokens | - |
| Embeddings - 150M-350M $0.016 / 1M input tokens | - |
| Embeddings - Qwen3 8B $0.1 / 1M input tokens | - |
| Training - Models up to 16B LoRA SFT: $0.50, LoRA DPO: $1.00, Full Param SFT: $1.00, Full Param DPO: $2.00 per 1M training tokens | - |
| Training - Models 16.1B-80B LoRA SFT: $3.00, LoRA DPO: $6.00, Full Param SFT: $6.00, Full Param DPO: $12.00 per 1M training tokens | - |
| Training - Models 80B-300B LoRA SFT: $6.00, LoRA DPO: $12.00, Full Param SFT: $12.00, Full Param DPO: $24.00 per 1M training tokens | - |
| Training - Models >300B LoRA SFT: $10.00, LoRA DPO: $20.00, Full Param SFT: $20.00, Full Param DPO: $40.00 per 1M training tokens | - |
| On Demand Deployments Pay per GPU second | - |
Signal by signal
| Signal | Fireworks AI | Sambanova |
|---|---|---|
| AgentReady | 59 | 48 |
| Discovery | 87 | 80 |
| Understanding | 38 | 38 |
| Adoption | 65 | 40 |
| Operability | 47 | 35 |
| Public API | Yes | Yes |
| MCP server | No | Yes |
| OpenAPI spec | Unknown | Yes |
| CLI | Yes | No |
| llms.txt | Yes | Yes |
| Self-serve signup | Yes | Unknown |
| Free tier | Yes | Unknown |
Which to pick
Fireworks AI clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Fireworks AI and Sambanova. Alternatives to each: Fireworks AI, Sambanova.
An agent can fetch this as data: POST /v1/compare {"slugs": ["fireworks", "sambanova"]}