identity

open weights

deepseek-chatDeepSeek

Name: deepseek-chat
Brand: DeepSeek
SKU: deepseek/deepseek-chat
Price: 0.1400 USD
Availability: InStock

from /1M in$0.14deepseek

context1M384K out

best ttft490msdeepseek

endpoints11 region

endpoints: 1
regions: 1
best tok/s: 77
api: chat
released: December 2024

capabilities 3/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

endpoints

1 / 1 region

Providers serving deepseek-chat, with pricing and measured performance. Best value in each column is coloured.
#										flags
1	DeepSeek	Global	1M	$0.14	$0.28	$0.03	490ms	77.0		no-train

provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Sep 12

median

hover the plot for weekly values

time to first token per provider: current value, window low and high, and change across the window
provider	now	low	high	change
DeepSeek	490ms	716ms	958ms	-5.3%

median wait before the first token lands. this is the number a user feels, and it moves with provider load through the day.

Lines are steps: each sample is one week of traffic held flat, not a slide from the week before. Click a name in the key to drop it from the plot. Measured through Sep 12.

benchmarks

artificial analysis

no published benchmark scores for this model

call it

model=

deepseek/deepseek-chat

this model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

openai compatible

main.py

1from openai import OpenAI2 3client = OpenAI(4    api_key="YOUR_REQUESTY_API_KEY",5    base_url="https://router.requesty.ai/v1",6)7 8response = client.chat.completions.create(9    model="deepseek/deepseek-chat",10    messages=[11        {"role": "user", "content": "Explain quantum computing in one paragraph."},12    ],13)14 15print(response.choices[0].message.content)

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models

notes

reference

An alias for DeepSeek v4 Flash in non-thinking mode.

questions 5

Which providers serve deepseek-chat?

deepseek-chat is available from 1 provider through Requesty: DeepSeek. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.

How much does deepseek-chat cost?

Pricing starts at $0.14 per million input tokens and $0.28 per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.

Is deepseek-chat open weights?

Yes. deepseek-chat is an open-weights model from DeepSeek, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.

What is the context window of deepseek-chat?

deepseek-chat supports up to 1M tokens of context, with up to 384K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.

How do I use deepseek-chat with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepseek/deepseek-chat" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.

more from deepseek 6

Other DeepSeek models
model	context	from /M	providers
deepseek-v4.1-flash	1.0M	$0.22	3
deepseek-v4-flash-vision-exp	1.0M	$0.22	1
deepseek-v4-pro-0813	1.0M	$1.30	4
deepseek-v4-flash-0731	1.0M	$0.07	8
deepseek-v4-pro-0424	1.0M	$1.04	4
deepseek-v4-flash-0424	1.0M	$0.07	4

route deepseek-chat through one endpoint

One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology