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GPT-5.6 Sol API: Endpoint & 25% Discount

Up to 25%

GPT-5.6 Sol is available on LLM.API as an OpenAI-compatible chat endpoint—route Gpt Sol quality through one key with transparent token pricing.

Compare GPT-5.6 Sol alternatives (30) →

What is GPT-5.6 Sol?

GPT-5.6 Sol is a Gpt Sol chat model exposed on LLM.API under id `gpt-5.6-sol`. Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows. Teams use it when they need reliable text generation with text, image inputs and text outputs over an OpenAI-compatible API.


Can you self-host GPT-5.6 Sol?

No. We found no public weights for GPT-5.6 Sol on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.

Skip the deploy — use LLM.API as your endpoint

No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, up to 25% below list price.

Providers

LLM.API routes GPT-5.6 Sol to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput
azure$4 in
$20 out
openai$4 in
$20 out
novita$4 in
$20 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
azurein $4; out $20 per 1M tokens1.1M tokensvision, tools, streaming, reasoning, web search, JSON, structured
openaiin $4; out $20 per 1M tokens1.1M tokensvision, tools, streaming, reasoning, web search, JSON, structured
novita25% offin $4; out $20 per 1M tokens1.1M tokensvision, tools, streaming, reasoning, web search, JSON, structured

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 11 Oct 2026.

Try this model

Test GPT-5.6 Sol right here — free to start.

GPT-5.6 Sol
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call GPT-5.6 Sol through the OpenAI-compatible API — POST /v1/chat/completions.

Switching from OpenAI? Change 2 lines.

- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"

Everything else stays the same — SDK, message format, tools, streaming. Set model to gpt-5.6-sol and the call runs unchanged.

bash
curl https://api.llmapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6-sol",
    "messages": [
      {"role": "user", "content": "Give me three crisp launch checklist items."}
    ],
  "reasoning_effort": "medium"
  }'
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAPI_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="gpt-5.6-sol",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.LLMAPI_KEY,
  baseURL: "https://api.llmapi.ai/v1",
});

const resp = await client.chat.completions.create({
  model: "gpt-5.6-sol",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

console.log(resp.choices[0].message.content);
stream = client.chat.completions.create(
    model="gpt-5.6-sol",
    messages=[{"role": "user", "content": "Write a haiku about latency."}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)
{
  "model": "gpt-5.6-sol",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ],
  "reasoning_effort": "medium"
}

Supported endpoints & features

Base URL https://api.llmapi.ai/v1 · model ID gpt-5.6-sol · OpenAI-compatible.

  • POST /v1/chat/completionsChat Completions — supported
FeatureStatusHow to set it
Function calling (tools)Supportedtools, tool_choice
Parallel tool callsNot supportedparallel_tool_calls
JSON modeSupportedresponse_format: {"type": "json_object"}
Structured outputsSupportedresponse_format: {"type": "json_schema", …}
StreamingSupportedstream: true
Vision (image input)Supportedimage_url content parts
Web searchSupportedweb_search
Reasoning effortnone · low · medium · high · xhigh · maxreasoning_effort: "medium" default medium

Errors & fallback routing

CodeWhat it meansWhat to do
401Missing or invalid API key.Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active.
429Rate limited, or the upstream provider is throttling the request.Back off and retry with jitter; the gateway also retries the request on another provider where one is available.
5xxUpstream provider error or timeout.Retry; fallback routing sends the retry to the next healthy provider for this model.

When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.

GPT-5.6 Sol in production

What the model is good at.

  • Tool-ready dialogue

    Works well in agent loops that call functions, browsers, or retrieval APIs. Reflects Gpt Sol positioning for this endpoint.

  • Analytical writing

    Produces clear analyses, comparisons, and decision memos from messy source material. Relevant for `gpt-5.6-sol` workloads on LLM.API.

  • Instruction following

    Follows detailed system and user instructions with strong adherence to format and tone. Tuned to how teams typically call GPT-5.6 Sol.

  • Conversational UX

    Maintains coherent multi-turn assistant behavior for product chat surfaces. Relevant for `gpt-5.6-sol` workloads on LLM.API.

  • Multi-step reasoning

    Breaks down complex problems into intermediate steps before answering. Grounded in the model's chat role rather than generic chat claims.

What you get when you call GPT-5.6 Sol through LLM.API.

  • Unified AI Routing

    Production: Reach GPT-5.6 Sol and sibling models through one OpenAI-compatible endpoint.

    One endpoint, every model.
  • Cost Control

    Practical: Compare provider price points and keep spend visible as you scale GPT-5.6 Sol.

    More performance, less spend.
  • Reliability Layer

    Practical: Retry and route across configured providers when a single upstream blips.

    Never go dark on users.
  • Observability

    Production: Trace prompts, tokens, and errors for GPT-5.6 Sol alongside the rest of your stack.

    See every token, everywhere.
  • Drop-in SDKs

    Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

    Think tasks, not models.
  • Model Breadth

    Practical: Swap GPT-5.6 Sol for chat, media, or embedding alternatives without rewriting auth.

    Scale from 1 to millions.

When to Use — When NOT to Use

Use it if...

  • Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (GPT-5.6 Sol)
  • You need a general-purpose text model for assistants, agents, or content workflows (GPT-5.6 Sol)
  • You want OpenAI-compatible chat completions through a single LLM.API key (GPT-5.6 Sol)
  • You need provider failover options exposed for this model id (GPT-5.6 Sol)

Avoid if...

  • You require on-prem only deployment with no cloud inference
  • Your use case depends on unpublished proprietary benchmarks not listed here
  • You need pure embedding, OCR, or media generation instead of chat
  • You need guaranteed real-time hard latency SLAs without benchmarking the provider

LLM API rating for GPT-5.6 Sol

★ 3.9/ 5.0LLM API rating
New release with no usage history yet · 60% category benchmark · 40% tooling & value
✓ Verified benchmark · Artificial Analysis
—Production adoptionNew frontier release — usage not tracked yet, excluded from the score
4.4Benchmark qualityArtificial Analysis Intelligence Index 47.0
3.3Developer ecosystemContext window, tool and JSON support, price against the category median
Reasoning & chat 3.9Coding 3.9Vision & multimodal 3.1Tool & function calling 4.3Long context 4.3
How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

  1. Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
  2. Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
  3. Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

GPT-5.6 Sol benchmark scores

Intelligence index

This model47.
Tracked median24.

Scale: 0-100 index points

Output speed

This model60 t/s

Scale: 0-400 tokens per second

Reference price per 1M tokens

Input$4.00
Output$20.00

Bars compare input and output list prices for this model.

Intelligence index+96% vs median
GPT-5.6 Sol: Self-Hosting & Deployment Guide47
Median tracked model24

Higher is better. The median covers every model tracked by Artificial Analysis.

Output speed
60tok/s

Measured throughput; the full dial is 300 tokens per second.

Reference price / 1M tokens
Input$4.00
Output$20.00

Provider list prices, before the LLM.API discount.

Independent scores published by Artificial Analysis (source). Reference prices are provider list prices, not LLM.API pricing.

GPT-5.6 Sol uptime, last 30 days

30-Day Uptime
96.70%
Past Incidents (30d)
3
Error rate (24h)
9.27%

Last 30 days

26/30 days operational | 96.70% uptime

Availability tracked for this model. Full history on the LLM Uptime Status page or the status hub. LLM.API routes around provider outages automatically.

What developers say about OpenAI models

LMArena—Speed60 tokens/sSources: LMArena, Artificial Analysis

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to GPT-5.6 Sol.

  • Long-horizon coding reports on GPT-6 Astra describe a clear step up over the GPT-5.x line, with the higher reasoning tiers seen as the sweet spot for planning and implementation in large (100K+ LOC) codebases.
  • The same field reports note that fast/ultra modes burn quota quickly and that very large refactors still stall, so teams tend to mix a cheap tier for routine calls with a reasoning tier for hard steps.
  • Community threads temper the hype: capability gains are acknowledged, but developers still report the usual failure modes on obscure reverse-engineering and modding work.

Frequently Asked Questions

  • Where is the canonical page for GPT-5.6 Sol?

    https://llmapi.ai/models/openai-gpt-5-6-sol/

  • Does GPT-5.6 Sol support streaming?

    Yes—at least one listed provider advertises streaming.

  • What is GPT-5.6 Sol?

    Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows. On LLM.API it is addressed as `gpt-5.6-sol`.

  • Is GPT-5.6 Sol a chat model?

    Yes—GPT-5.6 Sol is exposed as a chat/completions-style endpoint on LLM.API.

  • Which providers serve GPT-5.6 Sol?

    LLM.API currently lists: azure, openai. Availability can vary by region and account.

  • What modalities does GPT-5.6 Sol support?

    GPT-5.6 Sol accepts text, image and produces text according to its architecture metadata on LLM.API.

  • What is the context length for GPT-5.6 Sol?

    Reported context for GPT-5.6 Sol is 1.1M tokens. Always verify the active provider row if multiple providers are listed.

  • What are limitations of GPT-5.6 Sol?

    Like other API models, GPT-5.6 Sol can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • When should I choose GPT-5.6 Sol?

    You need a general-purpose text model for assistants, agents, or content workflows — especially when you specifically need GPT-5.6 Sol.

  • How is GPT-5.6 Sol priced on LLM.API?

    Listed pricing metadata shows: In $5.00 / 1M tokens · Out $30.00 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • Can I use tools or structured outputs with GPT-5.6 Sol?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

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