openrouter

dolphin3.0-r1-mistral-24b

completions

Dolphin 3.0 R1 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases. The R1 version has been trained for 3 epochs to reason using 800k reasoning traces from the Dolphin-R1 dataset. Dolphin aims to be a general purpose reasoning instruct model, similar to the models behind ChatGPT, Claude, Gemini. Part of the [Dolphin 3.0 Collection](https://huggingface.co/collections/cognitivecomputations/dolphin-30-677ab47f73d7ff66743979a3) Curated and trained by [Eric Hartford](https://huggingface.co/ehartford), [Ben Gitter](https://huggingface.co/bigstorm), [BlouseJury](https://huggingface.co/BlouseJury) and [Cognitive Computations](https://huggingface.co/cognitivecomputations)

Input:$0.01 / 1M tokens
Output:$0.03 / 1M tokens
Context:32768 tokens
text
text

Access dolphin3.0-r1-mistral-24b through LangDB AI Gateway

Recommended

Integrate with cognitivecomputations's dolphin3.0-r1-mistral-24b and 250+ other models through a unified API. Monitor usage, control costs, and enhance security.

Unified API
Cost Optimization
Enterprise Security
Get Started Now

Free tier available • No credit card required

Instant Setup
99.9% Uptime
10,000+Monthly Requests
Code Example
Configuration
Base URL
API Keys
Headers
Project ID in header
X-Run-Id
X-Thread-Id
Model Parameters
14 available
frequency_penalty
-202
include_reasoning
logit_bias
logprobs
max_tokens
min_p
001
presence_penalty
-201.999
repetition_penalty
012
seed
stop
temperature
012
top_k
top_logprobs
top_p
011
Additional Configuration
Tools
Guards
User:
Id:
Name:
Tags:
Publicly Shared Threads0

Discover shared experiences

Shared threads will appear here, showcasing real-world applications and insights from the community. Check back soon for updates!

Share your threads to help others
Popular Models10
  • deepseek
    DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs really well on a variety of tasks.
    Input:$0.18 / 1M tokens
    Output:$0.72 / 1M tokens
    Context:163840 tokens
    tools
    text
    text
  • deepseek
    May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass. Fully open-source model.
    Input:$0.18 / 1M tokens
    Output:$0.72 / 1M tokens
    Context:163840 tokens
    text
    text
  • deepseek
    DeepSeek-Chat is an advanced conversational AI model designed to provide intelligent
    Input:$0.27 / 1M tokens
    Output:$1.1 / 1M tokens
    Context:64K tokens
    tools
    text
    text
  • openai
    GPT-4o mini (o for omni) is a fast, affordable small model for focused tasks. It accepts both text and image inputs, and produces text outputs (including Structured Outputs). It is ideal for fine-tuning, and model outputs from a larger model like GPT-4o can be distilled to GPT-4o-mini to produce similar results at lower cost and latency.The knowledge cutoff for GPT-4o-mini models is October, 2023.
    Input:$0.15 / 1M tokens
    Output:$0.6 / 1M tokens
    Context:128K tokens
    tools
    text
    image
    text
  • openai
    OpenAI o4-mini-high is the same model as [o4-mini](/openai/o4-mini) with reasoning_effort set to high. OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains. Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.
    Input:$1.1 / 1M tokens
    Output:$4.4 / 1M tokens
    Context:200K tokens
    tools
    text
    image
    text
  • anthropic
    Our high-performance model with exceptional reasoning and efficiency
    Input:$3 / 1M tokens
    Output:$15 / 1M tokens
    Context:200K tokens
    tools
    text
    image
    text
  • anthropic
    claude-opus-4
    anthropic
    Our most capable and intelligent model yet. Claude Opus 4 sets new standards in complex reasoning and advanced coding
    Input:$15 / 1M tokens
    Output:$75 / 1M tokens
    Context:200K tokens
    tools
    text
    image
    text
  • gemini
    Gemini 2.5 Pro is our most advanced reasoning Gemini model, capable of solving complex problems.
    Input:$1.25 / 1M tokens
    Output:$10 / 1M tokens
    Context:1M tokens
    tools
    text
    image
    audio
    video
    text
  • openai
    gpt-4.1
    openai
    GPT-4.1 is OpenAI's flagship model for complex tasks. It is well suited for problem solving across domains.
    Input:$2 / 1M tokens
    Output:$8 / 1M tokens
    Context:1047576 tokens
    tools
    text
    image
    text
  • gemini
    Gemini 2.5 Pro Experimental is Google's state-of-the-art thinking model, capable of reasoning over complex problems in code, math, and STEM, as well as analyzing large datasets, codebases, and documents using long context.
    Input:$1.25 / 1M tokens
    Output:$10 / 1M tokens
    Context:1M tokens
    tools
    text
    image
    audio
    video
    text