Inference Pricing Analysis Shows 4.4x Spread for Same Model Across Providers

Inference Cost Analysis for AI Coding Agents
Analysis of inference pricing across multiple providers reveals significant cost variations for identical model outputs, with spreads reaching 4.4x for standard models and up to 30x for reasoning models.
Key Pricing Data from Source
For Llama 3.1 70B Instruct (same model, same weights):
- DeepInfra: $0.20 / $0.27 per million tokens
- Hyperbolic: $0.40 / $0.40 per million tokens
- Groq: $0.59 / $0.79 per million tokens
- Fireworks: $0.70 / $0.70 per million tokens
- Together: $0.88 / $0.88 per million tokens
This represents a 4.4x difference between the lowest (DeepInfra) and highest (Together) providers for the exact same API call.
Impact on Usage Costs
For a single agent processing approximately 10 million tokens per day:
- DeepInfra: ~$876/year
- Together: ~$3,212/year
Same output, same API call, but a difference of $2,336 annually.
Reasoning Model Price Spread
The analysis extends to reasoning models with even more aggressive pricing differences:
- DeepSeek R1 (Hyperbolic): ~$2 per 1 million output tokens
- OpenAI o1: ~$60 per 1 million output tokens
This represents approximately a 30x spread between providers.
Market Observations
The source notes that pricing moves more than expected week to week across providers, indicating there's no established "market price" yet for inference services. The author is currently tracking pricing for: DeepInfra, Hyperbolic, Groq, Fireworks, Together, OpenAI, Anthropic, and Akash.
Developer Considerations
The analysis raises practical questions for developers using AI coding agents:
- Locking into one provider vs. routing based on price
- Whether to actively track pricing or ignore the variations
- Which additional providers should be included in monitoring
📖 Read the full source: r/LocalLLaMA
👀 See Also

OpenClaw 2026.3.2 Release: Production Secrets, PDF Tool, and Safer Defaults
OpenClaw 2026.3.2 introduces a production-grade secrets system with fail-fast behavior, a native PDF tool with Anthropic and Google model support, and safer defaults that restrict tool access for new installations.

PS3 Emulator Devs Ask Devs to Stop Submitting AI-Generated PRs
RPCS3 maintainers have publicly requested users stop submitting pull requests generated by AI code agents, citing low quality and maintenance burden.

Open Source vs Frontier Models: Single-File Canvas Car Scene Benchmark
A developer tested 12 models including GPT-5.5, Claude Opus 4.7, and Qwen 3.6 Plus on a single-file HTML canvas car driving animation task, with results publicly compared.

SDNY Court Rules AI-Generated Legal Documents Not Protected by Privilege
Judge Jed S. Rakoff ruled that 31 documents generated using Anthropic's Claude AI tool were not protected by attorney-client privilege or work product doctrine, marking the first such court decision on AI-generated legal materials.