import osfrom openai import OpenAI client = OpenAI( base_url="https://model.graphn.ai/v1", api_key=os.environ["GRAPHN_API_KEY"],) reply = client.chat.completions.create( model="deepseek-v4.1-flash", messages=[{"role": "user", "content": "Hello"}],)
DeepSeek V4.1 Flash1M context
Kimi K2.5256K context
Mistral Large 3256K context
Qwen3 VL 235B256K context
Qwen3.8 27B256K context
+ Your model$ graphn model deploy
Managed inference · OpenAI-compatible API
Model launches
Oct 19, 2026DeepSeek V4.1 FlashLong-context reasoning, coding and agents, with image inputSep 28, 2026Kimi K2.5 (image)Frontier-scale agentic work with imagesSep 28, 2026Qwen3 VL 235B Instruct (image)Demanding image understanding and visual agentsSep 28, 2026Mistral Large 3Long-context assistants and enterprise agentsAug 14, 2026Qwen3.8 27B (image+video)Coding, long-horizon agents and image/video in one dense modelApr 20, 2026Qwen3-VL Embeddings (4096 dim, multimodal)Puts text, images, screenshots and video in one vector spaceApr 20, 2026Qwen3-VL Reranker (multimodal)Scores relevance across modalities, text against images and backApr 20, 2026Gemma 4 E4B (text+image+video+audio)The catalogue's audio-in model - speech and images without a separate ASR step
The built-in catalog
Chat & vision · 10
| Model | Context | Thinking | Tools | JSON | Vision | Audio | Input · 1M | Output · 1M |
|---|---|---|---|---|---|---|---|---|
DeepSeek V4.1 Flashdeepseek-v4.1-flash | 1M | · | · | $0.30 | $1.20 | |||
Kimi K2.5 (image)kimi-k2.5 | 256K | · | · | · | $0.60 | $3.00 | ||
Mistral Large 3mistral-large-3 | 256K | · | · | · | $0.50 | $1.50 | ||
Qwen3 VL 235B Instruct (image)qwen3-vl-235b | 256K | · | · | · | $0.53 | $2.66 | ||
Qwen3.8 27B (image+video)qwen3.8-27b | 256K | · | $0.45 | $3.20 | ||||
gpt-oss 120Bgpt-oss-120b | 128K | · | · | $0.15 | $0.60 | |||
Qwen3 80B Instructqwen3-80b | 128K | · | · | · | $0.20 | $0.60 | ||
Qwen3.5 9B Vision (image+video)qwen3-vl | 256K | · | $0.10 | $0.15 | ||||
Gemma 4 E4B (text+image+video+audio)gemma-4-e4b | 64K | · | $0.15 | $0.60 | ||||
GLM-5.3glm-5.3 | 1M | · | · | · | $1.40 | $4.40 |
Retrieval · 4
| Model | Kind | Input · 1M |
|---|---|---|
BGE Reranker v2bge-reranker | Text reranker | — |
BGE-M3 Embeddings (1024 dim)bge-m3 | Text embeddings | — |
Qwen3-VL Embeddings (4096 dim, multimodal)qwen3-vl-embedding | Text and image embeddings | — |
Qwen3-VL Reranker (multimodal)qwen3-vl-reranker | Text and image reranker | — |
Speech & OCR · 1
| Model | Kind | Input · 1M |
|---|---|---|
DeepSeek OCRdeepseek-ocr | Document OCR | — |
Every model has its own page with strengths, caveats, and a runnable request. The live list is in the app under Models, or via graphn model list-chat.
Your weights. Our muscle.
Deploy weights from Hugging Face or S3, LoRA included, behind the same API.
Custom model imports →
import graphn
See every request
Model, key, status, time to first token, tokens and cost for every call.
Call it from anywhere
OpenAI's request shape, so the tooling you already have works unchanged.
Models documentation →curl https://model.graphn.ai/v1/chat/completions \
-H "Authorization: Bearer $GRAPHN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-oss-120b",
"messages": [{"role": "user", "content": "Hello"}]
}'import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://model.graphn.ai/v1",
apiKey: process.env.GRAPHN_API_KEY,
});
const reply = await client.chat.completions.create({
model: "deepseek-v4.1-flash",
messages: [{ role: "user", content: "Hello" }],
});from graphn import chat
reply = await chat.complete(
"Explain async/await in one sentence.",
model="qwen3-80b",
temperature=0.2,
)Build agents on the same models
Grow a model call into a workflow with tools and knowledge bases.
The workflow platform →Support RouterRoute customer messages to the right specialist for orders, returns, or product questionsCompany Knowledge SearchAsk natural-language questions and get cited answers from your internal docsAutomated PR Review BotClone a repo, analyze a PR with a code-specialized model, synthesize review comments, and post them
Make your first call.
- 01
Create an account
$1 in credits to try inference, no card.
- 02
Add a card
$5 more in credits when you link a card.
- 03
Create an API key
Point any OpenAI SDK at GraphN and pick a model by name.