Fireworks AI vs Vespa
Fireworks AI scores higher on the AgentReady, 59/100 against 56/100. They differ on 4 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.
Vespa. Vespa.ai develops the Vespa AI Search Platform, a distributed serving engine that unifies retrieval, ranking, machine learning inference, and real-time serving for business-critical AI applications.
Where Fireworks AI is ahead
Fireworks AI passes authentication documented, and Vespa does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.
It also holds adopt: agent-compatible signup flow. Vespa misses it.
And on operate, structured, predictable output. Vespa misses it.
Where Vespa is ahead
Vespa passes structured api reference, and Fireworks AI does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.
What neither does
Both fail mcp discoverable, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, no mandatory sales call, programmatic credential creation, mcp integration available, 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. Both sit at 87/100 here. Fireworks AI misses mcp discoverable; Vespa misses mcp discoverable.
Understand. Vespa leads 46 to 38. Fireworks AI misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented; Vespa misses openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented.
Adopt. Fireworks AI leads 65 to 55. Fireworks AI misses no mandatory sales call, programmatic credential creation, mcp integration available; Vespa misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, mcp integration available.
Operate is whether an agent can run against it in production and recover when a call fails. Fireworks AI leads 47 to 35. Fireworks AI misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified; Vespa 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. Vespa starts at $0.05/hour with no free tier.
| Fireworks AI plans | Vespa plans |
|---|---|
| Serverless Inference Pay per token | Startup vCPU $0.05/hour, Memory GB $0.005/hour, Disk GB $0.0002/hour, GPU Memory GB $0.03/hour |
| Embeddings - up to 150M $0.008 / 1M input tokens | Basic vCPU $0.1/hour, Memory GB $0.01/hour, Disk GB $0.0004/hour, GPU Memory GB $0.07/hour |
| Embeddings - 150M-350M $0.016 / 1M input tokens | Commercial vCPU $0.145/hour, Memory GB $0.0145/hour, Disk GB $0.0005/hour, GPU Memory GB $0.1/hour |
| Embeddings - Qwen3 8B $0.1 / 1M input tokens | Enterprise vCPU $0.18/hour, Memory GB $0.018/hour, Disk GB $0.0007/hour, GPU Memory GB $0.125/hour |
| 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 | Self Managed Contact Sales |
| 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 | Vespa |
|---|---|---|
| AgentReady | 59 | 56 |
| Discovery | 87 | 87 |
| Understanding | 38 | 46 |
| Adoption | 65 | 55 |
| Operability | 47 | 35 |
| Public API | Yes | Yes |
| MCP server | No | No |
| OpenAPI spec | Unknown | Yes |
| CLI | Yes | Yes |
| llms.txt | Yes | Yes |
| Self-serve signup | Yes | Yes |
| Free tier | Yes | No |
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 Vespa. Alternatives to each: Fireworks AI, Vespa.
An agent can fetch this as data: POST /v1/compare {"slugs": ["fireworks", "vespa"]}