GPT-5.5 instant - ByteSpike

Vendor: OpenAI Model ID: gpt-5-5-instant Capability: 128K context · tool use · vision · streaming · structured output Pricing: per-token, flagship tier (live rate) GPT-5.5-instant is GPT-5.5 with the reasoning chain elided — the model goes straight from prompt to answer. For shorter prompts and tasks where the reasoning was overkill (extraction, structured output, short-form rewriting), this is the right pick: same flagship quality on bounded inputs, sub-second TTFB.

Request

curl https://llm.bytespike.ai/v1/chat/completions \
  -H "Authorization: Bearer $BYTESPIKE_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "gpt-5-5-instant",
    "messages": [{"role": "user", "content": "Rewrite this support response in a friendlier tone."}]
  }'

Body parameters

Field	Type	Required	Default	Notes
`model`	string	yes	—	`gpt-5-5-instant`
`messages`	array	yes	—	—
`max_tokens`	integer	no	model max	Max: 16384.
`tools`	array	no	—	Parallel function calling.
`response_format`	object	no	—	JSON / structured output.
`stream`	boolean	no	false	SSE streaming.

reasoning_effort is not accepted on this variant — passing it returns 422.

Response

{
  "id": "chatcmpl-…",
  "object": "chat.completion",
  "model": "gpt-5-5-instant",
  "choices": [{"index": 0, "message": {"role": "assistant", "content": "..."}, "finish_reason": "stop"}],
  "usage": {"prompt_tokens": 87, "completion_tokens": 142, "total_tokens": 229}
}

No reasoning_tokens field — there’s no reasoning chain.

Code examples

curl https://llm.bytespike.ai/v1/chat/completions \
  -H "Authorization: Bearer $BYTESPIKE_API_KEY" \
  -H "content-type: application/json" \
  -d '{"model": "gpt-5-5-instant", "messages": [{"role": "user", "content": "Rewrite this in a friendlier tone."}]}'

Streaming + caching

"stream": true for SSE. Sub-second TTFB on most prompts because the reasoning chain is elided. Automatic prompt caching on stable prefixes.

Errors

Code	Trigger	Billed?
400 / 401 / 402 / 429	Standard	No
422	Including `reasoning_effort` (use GPT-5.5 for reasoning)	No
5xx	Upstream	No (auto-retry)

When to use

Latency-critical surfaces where reasoning is overkill.
Short-form rewriting, extraction, structured output on bounded inputs.
For deeper multi-step reasoning, use GPT-5.5 with reasoning_effort.
For mini-tier cost on latency-bound work, see GPT-5.4-mini.

Limits

Limit	Value
Context window	128K tokens
Max output	16384 tokens
Supports tool use	Yes (parallel)
Supports vision	Yes
Supports streaming	Yes
Supports prompt caching	Automatic
Supports reasoning_effort	No

GPT-5.4 pro GPT-5.5

​Request

​Body parameters

​Response

​Code examples

​Streaming + caching

​Errors

​When to use

​Limits