DeepSeek V3.2: Make Math, Coding, and Problem-Solving Simple
Try DeepSeek V3.2 on Lorka to chat online to solve problems, generate code, handle logic-heavy tasks, and more while switching instantly between LLMs.
DeepSeek V3.2 is the reasoning-first family, available via the API as deepseek-chat (non-thinking) and deepseek-reasoner (thinking mode).
Try DeepSeek V3.2 on Lorka for Advanced Reasoning and Coding
Use DeepSeek V3.2 on our all-in-one platform as an AI newbie or an expert working with technical workflows to take advantage of state-of-the-art features, such as:
Advanced reasoning & logic
Coding-focused performance
Math & analytical solutions
Efficient code generation
Optimized for technical prompts
DeepSeek V3.2 Benchmarks for Coding and Math
Below are qualitative benchmark-style examples, in other words, prompts to output, that reflect where DeepSeek V3.2 programming and code generation perform best in practice.
This Python function should return only even numbers, but it crashes at runtime. Explain why and fix it so it works correctly. def filter_evens(values): result = [] for v in values: if v % 2 == 0: result.append(v) return result print(filter_evens(["1", "2", "3", "4", 5]))
The error occurs because the list contains strings and integers. The % operator only works on numbers. Convert each value to an integer before checking if it's even.
1def filter_evens(values):2 result = []3 for v in values:4 v = int(v)5 if v % 2 == 0:6 result.append(v)7 return result89print(filter_evens(["1", "2", "3", "4", 5])) # [2, 4]I roll a fair six-sided die twice. What's the probability the sum is 9?
Possible pairs that sum to 9: (3,6), (4,5), (5,4), (6,3) → 4 outcomes. Total outcomes: 6×6 = 36. Probability = 4/36 = 1/9 ≈ 0.111…
You have 3 tasks: A takes 30 min, B takes 45 min, C takes 20 min. You have 60 minutes. What's the best plan if you want to finish the most tasks?
To maximize completed tasks within 60 minutes, choose the shortest tasks first. C (20) + A (30) = 50 minutes → 2 tasks completed. Any plan including B (45) leaves only 15 minutes, so you finish just 1 task. Best plan: do C then A.
Write a short incident update in 4 bullet points: 1) what happened, 2) impact, 3) mitigation, 4) next update time. Keep it concise.
- What happened: Elevated error rates were detected on the API.
- Impact: Some users experienced failed requests and timeouts.
- Mitigation: Rolled back the latest deployment and restarted affected services.
- Next update: Another status update in 30 minutes.
Get More Out of DeepSeek V3.2 With Lorka
DeepSeek V3.2 is powerful on its own, but chatting on Lorka gives you the opportunity to switch with other LLMs instantly on a state-of-the-art interface. Here's what you get:
Try DeepSeek V3.2 Instantly
Test out your prompts and real workloads right away with DeepSeek V3.2, so you can see how the LLM performs.
Optimized for reasoning-heavy prompts
DeepSeek V3.2 is a reasoning-first model, and Lorka's prompt modes are designed to surface that strength for math, logic, and step-by-step problem-solving.
Strong performance on coding and math tasks
If you're comparing models for coding benchmarks, logic questions, or analytical workflows, the DeepSeek V3.2 coding model consistently delivers verifiable outputs instead of guesswork.
One platform, multiple top models
Switch between DeepSeek V3.2, GPT-5.1, Claude, Mistral, Llama, and more, all in the same chat in Lorka, without losing context.
Privacy-first by design
Your prompts stay private. Lorka doesn't train on your data or monetize your conversations.
Clean interface, no ads or clutter
A focused UI built for thinking, coding, and problem-solving without distractions.
Prompt-optimized modes for better results
Use preset modes tailored for coding, reasoning, analysis, and structured text to get stronger outputs with less prompt tweaking.
DeepSeek V3.2 Model Specs at a Glance
Model Type
- DeepSeek V3.2 is the reasoning-first family and is available via the API as deepseek-chat (non-thinking) and deepseek-reasoner (thinking mode)
Context Length
- Up to 128K tokens (with 164K tokens mentioned for experimental/Speciale variants)
Strengths
- Strong performance in coding, math, complex logic, and structured reasoning, often highlighted as best-in-class for "verifiable" tasks
- DeepSeek Sparse Attention (DSA) reduces compute for long-context scenarios while preserving quality
Limitations
- Not "full multimodal" generation as it can read images/docs but doesn't generate images/audio/video. "Thinking mode" may be slower and consume more tokens
- It also has region-specific guardrails on sensitive topics
Training
- DeepSeek positions V3.2 as "reasoning-first" with tool-use-oriented behavior
- the detailed training methodology isn't fully disclosed in a single public spec, so treat specifics beyond this as unconfirmed
What You Can Do With DeepSeek V3.2 on Lorka
Review practical use cases that give you an idea of how you can use DeepSeek V3.2 online on Lorka.
Complete analysis with advanced math & logic reasoning
Solve complex mathematical and logical questions step by step, with clear reasoning that you can verify.
Explain how to solve this probability problem and show each step clearly.
"Clean code generation on demand
Use DeepSeek V3.2 to create code with Python and other languages to generate usable, structured code for scripts, utilities, or small features without unnecessary output.
Generate a Python function that validates email addresses and includes basic error handling.
"Coding help for problems as a developer
Get clear explanations and fixes when code breaks, instead of vague suggestions.
Here's my error message. Explain what's causing it and rewrite the function so it works.
"Research Q&A with structured answers
Ask technical or academic questions and get explanations that are organized and easy to study.
Explain the difference between supervised and unsupervised learning with simple examples.
"Document summarization for fast understanding
When researching or preparing a professional presentation, turn long articles, reports, or PDFs into concise summaries with key takeaways.
Summarize this article in 6 bullet points and list the main conclusions.
"Analytical reasoning and decision support
If you are an analyst, DeepSeek on Lorka can help you work through scenarios, trade-offs, and constraints with logic-first responses.
Given these options and constraints, explain which choice makes the most sense and why.
"Structured planning and technical writing
Create outlines, specs, or step-by-step plans that stay focused and logically consistent as a technical writer.
Create a clear technical outline for a feature that allows users to export data securely.
"DeepSeek V3.2 vs. Other AI Models on Lorka
Below, you can review how DeepSeek compares with other top LLMs that can be used on Lorka.
| Models | Reasoning | Speed | Multimodality | Context | Ideal use cases |
|---|---|---|---|---|---|
DeepSeek V3.2 | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Competitive coding, math/logic, structured reasoning, technical analysis, long-context problem-solving. |
Grok 4.1 | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Cultural insights, audience sentiment research, original content concepts, and fast analysis. |
Claude 3.x / 4.x | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Corporate communication, lengthy documents, contract-style content, and structured workflows. |
Gemini 3 | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Deep research analysis, uncovering insights, and complex expert-level work. |
GPT-5.2 | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Stronger reasoning and better instruction-following for reports, coding, debugging, analysis, and summaries. |
GPT-5.1 | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Tasks that need quick delivery but still demand careful, high-quality reasoning. |
GPT-5 | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| In-depth writing, complex planning, and creating smart system-style outputs. |
GPT-4o | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Real-time translation and efficient user support. |
Mistral Large | 💡💡💡💡💡 | ⚡⚡⚡⚡⚡ | 🤖🤖🤖🤖🤖 | 🧠🧠🧠🧠🧠| Language-centric tasks and scalable, cost-effective production workflows. |
DeepSeek V3.2
Competitive coding, math/logic, structured reasoning, technical analysis, long-context problem-solving.
Grok 4.1
Cultural insights, audience sentiment research, original content concepts, and fast analysis.
Claude 3.x / 4.x
Corporate communication, lengthy documents, contract-style content, and structured workflows.
Gemini 3
Deep research analysis, uncovering insights, and complex expert-level work.
GPT-5.2
Stronger reasoning and better instruction-following for reports, coding, debugging, analysis, and summaries.
GPT-5.1
Tasks that need quick delivery but still demand careful, high-quality reasoning.
GPT-5
In-depth writing, complex planning, and creating smart system-style outputs.
GPT-4o
Real-time translation and efficient user support.
Mistral Large
Language-centric tasks and scalable, cost-effective production workflows.
Strengths and Weaknesses of DeepSeek V3.2 and Other AI Models
DeepSeek V3.2
Exceptional for "verifiable" tasks, such as math, logic, and coding, especially when you need structured, step-by-step problem-solving.
Not fully multimodal as image generation is only available on Janus Pro, and deeper "thinking" style runs can be slower and use more tokens.
Gemini 3
Excellent long-context handling and multimodal reasoning, with strong coding and tool-use benchmarks.
The ecosystem and docs are still catching up with OpenAI's advancements.
GPT-5.2
A frontier model designed for better reasoning with efficient instruction-following compared to 5.1 for writing, coding, and more.
More resource-intensive than lighter models, with some workflows better suited to faster "instant" alternatives when quick delivery is essential.
GPT-5.1
New "Instant vs. Thinking" modes give an excellent balance of speed and deep reasoning for strong coding & tool-calling performance.
Reasoning mode can be slower and more expensive, and some multimodal workflows are still evolving relative to GPT-5's full stack.
GPT-5
Great for frontier-level multimodal reasoning, large context window, and advanced agentic capabilities for complex, multistep tasks.
Usually considered as "overkill" for simple chat or lightweight apps.
GPT-4o
Excellent speed and latency with strong multimodal support (text, images, audio, video), very good general-purpose assistant.
Smaller context and slightly weaker reasoning than the newest frontier models.
Claude 3.x / 4.x
Very strong reasoning and coding, that typically matches or beats other top models on some benchmarks when using Claude 4.5.
Multimodal support and ecosystem integrations are improving, but are less expansive than OpenAI's meaning speed can be lower at higher-precision settings.
Grok 4.1
Well-suited for understanding live trends and public opinion to deliver fast, context-aware responses that support analysis and extended writing tasks.
The ecosystem is still improving, and multimodal functionality may not be consistently available across all environments.
Mistral Large
Strong multilingual performance, good reasoning for text tasks, flexible deployment options, and generally cheaper usage compared to many frontier models.
Primarily text-first, with a more limited multimodal support. Its context window and ecosystem are mostly behind the very largest proprietary models.
Llama 3.2 / 4
Strong coding and reasoning in Llama 4, and solid multimodal vision support in 3.2 Vision, which is well-suited for fine-tuning and custom, privacy-sensitive deployments.
Out-of-the-box quality is typically a step below the latest closed-loop frontier models. Its performance depends heavily on hosting, tuning, and prompt engineering.