deepseek-v4-pro
Lyceum/🇪🇺 EU/chat
DeepSeek V4 Pro is DeepSeek's flagship Mixture of Experts model (1.6T total, 49B active parameters) with a 1M token context window, built for advanced reasoning, coding, and long-horizon agentic workflows with strong tool use. Served by Lyceum in the EU.MoreLess
Which id to call
lyceum/deepseek-v4-proThis exact deployment on Lyceum, with no routing and no failover. Send it as the model field.
Input /1M
$1.75
$0.44 cached
Output /1M
$3.50
2.0x input
Context
1.0M
66K output
Added
Apr 2026
chat
Capabilities 4/8
Provider rates
What deepseek-v4-pro costs
Provider prices per 1M tokens, updated October 30, 2026.moreless
These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.
Input /1M
$1.75
Output /1M
$3.50
Cache write /1M
-
Cache read /1M
$0.44
What a workload costs
- 100K input + 10K output
- $0.21
- 1M input + 100K output
- $2.10
- 10M input + 1M output
- $21.00
At the rates above, before caching. A cache read costs $0.44 per 1M, so repeated context lands under these figures.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
lyceum/deepseek-v4-proThis exact deployment on Lyceum, with no routing and no failover. Send it as the model field.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="lyceum/deepseek-v4-pro", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Reference
Specs and data terms
What the catalog reports for this deployment, and what the provider does with the traffic.
Released 2026-08-13
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.
Same provider
More from Lyceum
Newest first, on the same provider and the same key.
Reference
deepseek-v4-pro questions
How much does deepseek-v4-pro cost?
deepseek-v4-pro is priced at $1.75 per million input tokens and $3.50 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
What is the context window of deepseek-v4-pro?
deepseek-v4-pro has a context window of 1.0M tokens, with a maximum output of 66K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
How does deepseek-v4-pro perform on benchmarks?
deepseek-v4-pro scores 92.8% on GPQA Diamond, 51.0% on SciCode, 41.0% on Humanity's Last Exam. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can deepseek-v4-pro do?
deepseek-v4-pro supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use deepseek-v4-pro 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 "lyceum/deepseek-v4-pro". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run deepseek-v4-pro through Requesty?
Yes. deepseek-v4-pro runs through Requesty's OpenAI-compatible API, served from Lyceum. You do not host the model yourself: point base_url at Requesty, set the model to "lyceum/deepseek-v4-pro", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call deepseek-v4-pro through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.