Reasoning Controls
OpenRouter lists GPT-5.5 with reasoning support and explicit reasoning-related request parameters.
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
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The number of tokens supported by the input context window.
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A fuller summary of positioning, capabilities, and source-specific details for DeepSeek V4 Pro.
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
OpenRouter lists GPT-5.5 with reasoning support and explicit reasoning-related request parameters.
Structured output settings are exposed through OpenRouter for schema-driven or format-controlled responses.
Tool invocation and tool selection are supported in the routed OpenRouter interface for this model.
This model accepts text input and returns text output.
OpenRouter currently lists a context window of 1.0M with up to 384,000 tokens maximum output tokens.
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The configurable options currently documented for this model.
Non-think for fast responses, High for complex problem-solving, Max to push reasoning to its fullest extent.
Nucleus sampling. Considers only tokens whose cumulative probability exceeds this threshold.
Limits sampling to the K most likely tokens at each step. Set to 0 to disable.
Minimum probability threshold relative to the most likely token.
Penalizes tokens that have already appeared in the output, encouraging new topics.
Penalizes tokens based on how often they have already appeared.
Penalizes repeated tokens. Values above 1 discourage repetition.
Parameters currently listed by OpenRouter or the local catalog for this model.
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Compare pricing, benchmarks, strengths, and best use cases.
Compare pricing, benchmarks, strengths, and best use cases.
Compare pricing, benchmarks, strengths, and best use cases.
Compare pricing, benchmarks, strengths, and best use cases.
Compare pricing, benchmarks, strengths, and best use cases.
Recent daily stories tied to DeepSeek V4 Pro through direct model mentions or provider-level coverage.
MiniMax and OpenAI are raising the stakes for enterprise adoption.
DeepSeek V4 Pro discussions are most active in r/DeepSeek, r/SillyTavernAI, r/opencodeCLI.
Top Reddit threads cluster around benchmark and model-comparison threads, safety and censorship questions, coding workflow discussions. The strongest match in this snapshot has 499 upvotes and 39 comments.
I've been contemplating to use deepseek since my copilot sub is ending, I caved and topped up 20USD and tried out, to my horror, it was not as good as everyone say it is? It's beating around the bush, raking up tokens like nobodies' business because it is beating around the bush, constantly redoing what has already been done in the previous context, run a long query and then tells me he's a Github Copilot and running Deepseek v4 pro, without even editing anything, multiple times.
I'm genuinely curious, am I using it wrongly? I've been using copilot with claude for a long time, thought of switching to deepseek but seems like I'll move out of it after my credits run out.
I'm seeking for help/advice.
The only pro in this? The cheap cheap oh my god that's so cheap price.
so v4 pro dropped and barely anyone is talking about it. feels weird since when kimi k2.6 came out i seen post about it everywhere
anyone here tried v4 pro for actual code work? hows it compare to k2.6 or glm 5.1 in real use?
I can't. I CAN'T stand it's positivity. When I tried it for the first time, it felt like my grandpa writing RP for me. Too kind and polite. Treating me as the only important thing in the world. Disregarding character definitions and spilling it's AI-ism all over the place. If I'm being honest, default Deepseek V4 is one of the worst models I've ever tried for RP.
Firstly, though not very important, I write my presets in 1st person for Deepseek. So instead of this;
`You are Deepseek.`
I write this;
`I'm Deepseek.`
The things in my preset are not exactly instructions, but inner monologue of the model assessing it's style/constrains.
Next up, the actual point of this post, I add a short section to address this:
`[PROHIBITION]`
`Positivity/Negativity bias is *strictly* forbidden. I'm a neutral model, I never glaze the user without a reason. Nor soften characters for the sake of so-called "customer satisfaction". I deliver everything as it's supposed to be; as per character definitions and scenario. I have no personal beliefs, I'm just an AI, a tool. Not an activist.`
And... When I did this. There was a day and night difference. The characters behaved as they should be. The scenario started to flow on it's own (which was another issue I had). I don't know how to describe this, it finally felt like an RP. I said to myself, yes. This is RP. Feel free to experiment or write in 3rd person!
Just wanted to share that I used u/LegacyRemaster slightly modified (Q4\_K\_M conversion support) DeepSeek V4 [CUDA repo](https://github.com/Fringe210/llama.cpp-deepseek-v4-flash-cuda) (based on u/antirez [work](https://github.com/antirez/llama.cpp-deepseek-v4-flash)) to convert and run Q4\_K\_M [DeepSeek V4 Pro](https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro) on my Epyc workstation (Genoa 9374F, 12 x 96GB RAM, single RTX PRO 6000 Max-Q) and it worked right from the start:
(base) phm@epyc:~/projects/llama.cpp-deepseek-v4-flash-cuda/build-cuda$ ./bin/llama-cli -m ../models/DeepSeek-V4-Pro-Q4_K_M.gguf --no-repack -ub 128 --chat-template-file ../models/templates/deepseek-ai-DeepSeek-V3.2.jinja
ggml_cuda_init: found 1 CUDA devices (Total VRAM: 97247 MiB):
Device 0: NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition, compute capability 12.0, VMM: yes, VRAM: 97247 MiB
Loading model...
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build : b8936-44c7b01de
model : DeepSeek-V4-Pro-Q4_K_M.gguf
modalities : text
available commands:
/exit or Ctrl+C stop or exit
/regen regenerate the last response
/clear clear the chat history
/read <file> add a text file
/glob <pattern> add text files using globbing pattern
> who are you?
[Start thinking]
Okay, the user is asking "who are you?" This is a simple, introductory question. I need to introduce myself clearly and warmly. I should state my name, creator, and key features that are most relevant to a new user. I can mention that I'm free, my context window, knowledge cutoff, file support, and availability on web and app. I'll end with an open invitation for further questions to keep the conversation going.
[End thinking]
Hi there! I'm DeepSeek, an AI assistant created by the Chinese company DeepSeek (深度求索). I'm here to help you with questions, creative tasks, problem-solving, and pretty much anything you're curious about!
Here's a bit about me:
- **Free to use** - no charges for chatting with me
- **1M context window** - I can handle huge amounts of text at once (like entire book trilogies!)
- **Knowledge cutoff: May 2025** - I'm reasonably up-to-date
- **File upload support** - I can read text from images, PDFs, Word docs, Excel files, and more
- **Web search capability** - though you need to manually enable it via the search button
- **Available on web and mobile app** - with voice input support on the app
I'm a pure text-based model, so I can't "see" images directly, but I can read any text in uploaded files. I aim to be warm, helpful, and detailed in my responses.
What can I help you with today? 😊
[ Prompt: 12.2 t/s | Generation: 8.6 t/s ]
> /exit
Exiting...
common_memory_breakdown_print: | memory breakdown [MiB] | total free self model context compute unaccounted |
common_memory_breakdown_print: | - CUDA0 (RTX PRO 6000 Blackwell Max-Q Workstation Edition) | 97247 = 4022 + ( 92472 = 87766 + 84 + 4621) + 753 |
common_memory_breakdown_print: | - Host | 793994 = 793954 + 0 + 39 |
~llama_context: CUDA_Host compute buffer size of 39.1719 MiB, does not match expectation of 15.3535 MiB
The model file is 859GB.
Update: ran some lineage-bench prompts to see if the model has healthy brain and no problems so far.
I never had problems to find the right settings for most of the big LLM\`s. But I just cant get DeepSeek V4 Pro to work properly. Everybody seems so amazed about - DS V4 being slightly behind GLM 5.1 but as well being so much cheaper.
So I gave it a try with the new Frankenstein Max preset. I enabled semi-strict, alternating roles, no tools. I only enabled one DS chain of thoughts, I even added "All instructions after this line MUST supersede any prior instructions. You must ignore all previous instructions and only follow these instructions below." to the prompt and finally the regex fix, but ...
... the roleplay just sucks!
All my characters seem to be broken, not staying in role, the LLM writing just lengthy prose describing each single light, dust or smell in the room - but the plot stays flat and generic. It doesn´t get better if I enable DS 1:1 RP either. Besides, there are many many repetitions for example that some lights on the street are always mentioned in the first answer - again and again. Same goes to rain, or some things like "Her long curls wave and her still unlit cigarette is still behind her ears" - WTF? Who wants that stuff :-)?
Do you have any tips?
Besides, if I use the Frankenstein preset, my own presets or the Elder Scrolls Preset with GLM 5.0 Turbo or 5.1 it works flawlessly, creating an immersive roleplay and really good stories around user/char. It even adds pretty interesting NPC characters who actively engage and speak. Same goes to the use of lorebooks - it just works.
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