# DeepInfra — Provider Research (Phase 0)

Researched 2026-07-30 against official docs (https://docs.deepinfra.com — note: deepinfra.com/docs/* now 308-redirects there) and a live authenticated GET /v1/openai/models probe (/tmp/zyquo-probe/deepinfra.json, 174 models, mixed modalities). Each entry embeds metadata.context_length, metadata.max_tokens, and metadata.pricing (USD per 1M tokens) — authoritative for existence, context, and pricing.

# 1. Base URL & Endpoints

• OpenAI-compatible base URL: https://api.deepinfra.com/v1/openai (what Zyquo Cloud uses)
  • POST /v1/openai/chat/completions
  • POST /v1/openai/completions
  • GET /v1/openai/models
  • POST /v1/openai/embeddings (out of scope)
• Native inference endpoints also exist (https://api.deepinfra.com/v1/inference/{model}) with per-model schemas — documented for completeness only; Zyquo Cloud uses the OpenAI-compatible surface exclusively.

Reference: https://docs.deepinfra.com/chat/overview

# 2. Authentication

Authorization: Bearer <DEEPINFRA_TOKEN> — standard Bearer. Confirmed by docs and live probe.

# 3. Chat Model Catalog (curated main chat models)

Notable: DeepInfra proxies Anthropic Claude and Google Gemini models under its own billing — useful as a single-key fallback. Pricing/context below are from the live probe (metadata), USD per 1M tokens. metadata.max_tokens equals context_length for every chat entry (listing does not expose a distinct max-output figure — treat real max output as unverified per model). Caps legend: V vision, T tools, R reasoning, J JSON mode. All stream. Flags marked * inferred from model family, not individually verified on DeepInfra.

# Proxied frontier models

# Open-weight chat models

Also present (skip or list under "more"): Hermes-3 405B/70B, Llama-Guard-4 (moderation), MythoMax, Sao10K roleplay models, gemma-4 turbo/ultra variants, deepcogito, Qwen3-32B/30B-A3B/14B, etc.

# 4. Request/Response Format

OpenAI-compatible. Point any OpenAI SDK at base_url=https://api.deepinfra.com/v1/openai. Standard choices[].message, usage, finish_reason. Docs caveat: "We may not be 100% compatible with all OpenAI parameters" — unknown params are generally ignored. DeepInfra also has native per-model inference endpoints (/v1/inference/{model}) with different schemas — not used by Zyquo Cloud.

Supported params include: model, messages, max_tokens, temperature (0–2), top_p, stop, n, presence_penalty, frequency_penalty, stream, response_format (JSON mode), tools/tool_choice, reasoning_effort (reasoning models). Reasoning models return chain-of-thought as message.reasoning_content (DeepSeek convention; verify per model in Phase 7 — unverified field name for non-DeepSeek models).

# 5. Streaming

(https://docs.deepinfra.com/chat/streaming)

• stream: true → OpenAI-style SSE: data: {chunk} lines with choices[].delta.content, final data: [DONE].
• Usage is included automatically in the final chunk before [DONE] (when finish_reason is populated; token counts match non-streaming). No stream_options.include_usage needed (parameter not documented; sending it is harmless).
• On completion the delta becomes {} and finish_reason is set.

# 6. Special Parameters

• service_tier: "priority" (faster TTFT/throughput, +50% price) or "flex" (−20% price, may queue up to ~10 min). Default tier if omitted.
• fail_fast: true — reject immediately with HTTP 429 ("engine_overloaded" code) instead of queueing when capacity is exceeded; rejected requests are not billed.
• Response continuation pattern: to continue a truncated answer, resend with the truncated assistant message appended (documented technique, not a parameter).
• reasoning_effort supported on reasoning-capable models (gpt-oss etc.).
• Prompt caching: automatic on supported models; discounted cached_input_tokens pricing appears in the model metadata (no request parameter required — unverified whether a cache-control knob exists).

# 7. Rate Limits & Errors

(https://deepinfra.com/docs/advanced/rate-limits)

• 200 concurrent requests per account (the primary limit; no published RPM/TPM). Increases via Dashboard → Account request.
• Exceeding it → HTTP 429 "Rate limited"; capacity overload with fail_fast → 429 "engine_overloaded".
• Errors are OpenAI-shaped JSON; branch on HTTP status (400/401/404/429/5xx). Retry with backoff on 429/5xx.

# 8. /models Listing

GET https://api.deepinfra.com/v1/openai/models returns OpenAI shape {"object":"list","data":[...]} — but each model carries a rich non-standard metadata object:

{
  "id": "deepseek-ai/DeepSeek-V4-Pro",
  "object": "model",
  "owned_by": "deepinfra",
  "metadata": {
    "description": "...",
    "context_length": 1048576,
    "max_tokens": 1048576,
    "pricing": { "input_tokens": 1.3, "output_tokens": 2.6, "cached_input_tokens": 0.1 }
  }
}

Ideal for dynamic refresh: filter entries where metadata.context_length and pricing.output_tokens are non-null (text-gen models); image/video/TTS/ASR entries have null context/pricing fields. No capability flags (vision/tools) — keep those in the built-in catalog.