Most powerful LLMs (Large Language Models)
Read Time 23 mins | Written by: Cole
[Last updated: March 2025]
The LLMs (Large Language Models) underneath the hood of ChatGPT, Claude, Copilot, Cursor, and other generative AI tools are the main tech your company needs to understand.
LLMs make chatbots possible (internal and customer-facing), can assist in increasing coding efficiency, and are the driving force behind why Nvidia exploded into the most valuable company in the world.
Model size, context window size, performance, cost, and availability of these LLMs determine what you can build and how expensive it is to run.
Here are the important stats of the most powerful LLMs available – from proprietary to the world’s best open-source models.
LLMs (Large Language Models) for enterprise systems
OpenAI LLMs
ChatGPT and OpenAI are household names when it comes to large language models (LLMs). They started the generative AI firestorm with $10 billion in Microsoft funding and their GPT models have been at the top of the best LLMs available ever since.
|
Model |
Size |
Context Window |
Max Output Tokens |
Knowledge Cutoff |
Strengths & Features |
Cost (per m tokens, Input/Output) |
|
12.8 trillion |
128,000 tokens |
16,384 tokens |
Sep 30, 2023 |
Largest GPT model, deep world knowledge, excels in creative tasks, writing, open-ended reasoning
|
$75.00 / $150.00 |
|
|
~1.8 trillion |
128,000 tokens |
16,384 tokens |
Sep 30, 2023 |
Fast, intelligent, versatile model; excels across various tasks; best general-purpose model
|
$2.50 / $10.00 |
|
|
Not public |
200,000 tokens |
100,000 tokens |
Sep 30, 2023 |
High-intelligence reasoning model with internal "chain of thought"; optimized for complex problem-solving
|
$15.00 / $60.00 |
|
|
Not public |
128,000 tokens |
65,536 tokens |
Sep 30, 2023 |
Faster, affordable variant of o1; designed for quicker reasoning tasks at lower costs
|
$1.10 / $4.40 |
|
|
Not public |
200,000 tokens |
100,000 tokens |
Sep 30, 2023 |
Newest small reasoning model; superior performance at low latency/cost; enhanced developer features |
$1.10 / $4.40 |
Anthropic LLMs
Anthropic was founded by ex-OpenAI VPs who wanted to prioritize safety and reliability in AI models. They moved slower than OpenAI but their Claude 3 family of LLMs were the first to take the crown from OpenAI GPT-4 on the leaderboards in early 2024.
Anthropic released Claude 3.7 Sonnet to outperform GPT-4o and Claude is a consistent favorite for advanced coding tasks and reliable enterprise tools.
|
Model |
Parameters |
Context Window |
Max Output |
Knowledge Cutoff |
Strengths & Features |
Cost (per m tokens, Input/Output) |
|
~175 billion |
200k tokens |
Normal: 8,192 Extended Thinking: 64,000 (128,000 tokens with beta API) |
Oct 2024 |
Highest intelligence, extended reasoning, excels in complex problem-solving |
$3.00 / $15.00 |
|
|
Not public |
200k tokens |
8,192 tokens |
Apr 2024 |
High intelligence and balanced performance for complex tasks
|
$3.00 / $15.00 |
|
|
Not public |
200k tokens |
8,192 tokens |
Jul 2024 |
Fastest model, optimized for rapid responses and moderate complexity
|
$0.80 / $4.00 |
|
|
Not public |
200k tokens |
4,096 tokens |
Aug 2023 |
Top-tier intelligence, fluency, detailed analysis for intricate problem-solving
|
$15.00 / $75.00 |
Google LLMs
Google was notoriously far behind on commercial LLMs – even though a Google team developed the revolutionary transformer technology that makes LLMs possible. They’ve since caught up in capabilities with the Gemini family multimodal models and their 1-2 million token context windows.
| Model | Max Input Tokens (Context Window) | Max Output Tokens | Knowledge Cutoff | Strengths & Features | Modalities Supported (Input → Output) | Cost |
|---|---|---|---|---|---|---|
| Gemini 2.0 Pro | 2,097,152 tokens (2M) | 8,192 tokens | June 2024 |
Strongest Google model for coding, extensive world knowledge, optimized for extremely long contexts.
|
Text, Images, Video, Audio, PDF → Text | Custom |
| Gemini 2.0 Flash | 1,048,576 tokens (1M) | 8,192 tokens | June 2024 |
High-speed, multimodal performance optimized for real-time streaming and everyday tasks.
|
Text, Images, Audio, Video, PDF → Text (Audio preview only) | Custom |
| Gemini 2.0 Flash-Lite | Not specified | Not specified | Jan. 2025 |
Cost-effective model optimized for high throughput and scalable general-purpose tasks.
|
Text, Images, Audio, Video, PDF → Text | Custom |
| Gemini 2.0 Flash Thinking | 1,048,576 tokens (1M) | 65,536 tokens | May 2024 |
Enhanced reasoning capabilities with explicit reasoning steps included in responses.
|
Text, Images → Text | Custom |
Mistral LLMs
Mistral AI is a leading French AI company specializing in developing cutting-edge large language models (LLMs) designed for efficiency, performance, and accessibility. With a strong commitment to open-source innovation and affordable premium offerings, Mistral AI has positioned itself as a leading provider in the AI ecosystem, catering to both enterprise and community-driven use cases.
|
Model |
Parameters |
Context Window |
Max Output Tokens |
Knowledge Cutoff |
Strengths & Features |
Cost (per m tokens, Input/Output) |
|
Not publicly disclosed |
256,000 tokens |
Not specified |
Jan 2025 |
Specialized coding model optimized for low-latency tasks like code correction and test generation.
|
$0.0003 / $0.0009 |
|
|
Not publicly disclosed |
131,000 tokens |
Not specified |
Nov 2024 |
Top-tier reasoning model ideal for high-complexity analytical tasks.
|
$0.002 / $0.006 |
|
|
Not publicly disclosed |
131,000 tokens |
Not specified |
Nov 2024 |
Multimodal model combining vision and text understanding with advanced reasoning capabilities.
|
$0.002 / $0.006 |
|
|
Not publicly disclosed |
32,000 tokens |
Not specified |
Feb 2025 |
Optimized for Middle Eastern and South Asian languages; powerful and efficient for regional use cases.
|
$0.0002 / $0.0006 |
|
|
3 billion |
131,000 tokens |
Not specified |
Oct 2024 |
Highly efficient, optimized for resource-constrained edge applications.
|
$0.00004 / $0.00004 |
|
|
8 billion |
131,000 tokens |
Not specified |
Oct 2024 |
Strong edge performance with an exceptional performance-to-cost ratio. |
$0.0001 / $0.0001 |
Open source LLMs for enterprise
DeepSeek Open Source LLMs
DeepSeek shocked the AI community in 2025 by releasing the open-source model DeepSeek-R1, which demonstrated competitive performance against leading proprietary frontier models, challenging the traditional dominance of closed-source solutions.
Because of development in China and assertions from OpenAI, DeepSeek has some large security risks to account for before using for enterprise.
| Model | Parameters | Context Window | Knowledge Cutoff | Strengths & Features | License Type |
|---|---|---|---|---|---|
| DeepSeek-R1 | 671 billion (MoE) | 64K | 8k |
Excels in reasoning-intensive tasks, including code generation and complex mathematical computations.
|
MIT License |
| DeepSeek-V3 | Not publicly disclosed | 64K | 8k |
Outperforms other open-source models; achieves performance comparable to leading closed-source models.
|
MIT License |
| DeepSeek-Coder-V2 | 236 billion | 16k | Not specified |
Enhanced coding and mathematical reasoning abilities; pre-trained on 6 trillion tokens.
|
MIT License |
| DeepSeek-VL | Not publicly disclosed | Not specified | Not specified | Designed to enhance multimodal understanding capabilities. | MIT License |
Nvidia Open Source LLMs
Nvidia is known for their GPUs but they have a whole enterprise AI ecosystem – from dev tools to their NIM microservices platform. They had early entries into LLM space with ChatRTX and Starcoder 2 but their most powerful LLM offering is the Nemotron-4 340B model family.
| Model | Parameters | Context Window | Max Output Tokens | Knowledge Cutoff | Strengths & Features | Availability | License Type |
|---|---|---|---|---|---|---|---|
| Nemotron-4 340B Base | 340 billion | 4,096 tokens | 4,000 tokens | June 2023 |
Base model for synthetic data generation; trained on 9 trillion tokens across English texts, 50+ natural languages, and 40+ coding languages.
|
NVIDIA NGC, Hugging Face | NVIDIA Open Model License |
| Nemotron-4 340B Instruct | 340 billion | 4,096 tokens | 4,000 tokens | June 2023 |
Fine-tuned model optimized for English conversational AI (single- and multi-turn interactions).
|
NVIDIA NGC, Hugging Face | NVIDIA Open Model License |
| Nemotron-4 340B Reward | 340 billion | 4,096 tokens | 4,000 tokens | June 2023 | Multidimensional Reward Model designed for evaluating outputs and generating synthetic training data. | NVIDIA NGC, Hugging Face | NVIDIA Open Model Licens |
Meta Llama 3 Open Source LLMs
While Meta is commonly known for being a champion of open source in AI, their models are open weights and not true open source according to many. Either way, open weights still means you can run these models locally – which you can't do with OpenAI LLMs.
|
Model |
Parameters |
Context Window |
Max Output Tokens |
Knowledge Cutoff |
Strengths & Features |
License Type |
Cost |
|
70 billion |
128,000 tokens |
Not specified |
December 2023 |
General-purpose multilingual model with optimized transformer architecture, pretrained on 15T tokens.
|
Llama 3.3 Community License |
Free (open-source) |
|
|
70 billion |
128,000 tokens |
Not specified |
December 2023 |
Instruction-tuned multilingual model optimized for conversational tasks with RLHF fine-tuning.
|
Llama 3.3 Community License |
Free (open-source) |
|
|
1.23 billion |
128,000 tokens |
Not specified |
December 2023 |
Lightweight multilingual model, optimized for mobile AI applications, retrieval, summarization, and chat use cases.
|
Llama 3.2 Community License |
Free (open-source) |
|
|
3.21 billion |
128,000 tokens |
Not specified |
December 2023 |
Mid-sized multilingual model for agentic retrieval, summarization, conversational tasks, and efficient inference.
|
Llama 3.2 Community License |
Free (open-source) |
|
|
1.23 billion |
8,000 tokens |
Not specified |
December 2023 |
Quantized for highly constrained environments, optimized for mobile and edge use cases with minimal compute needs.
|
Llama 3.2 Community License |
Free (open-source) |
|
|
3.21 billion |
8,000 tokens |
Not specified |
December 2023 |
Efficiently quantized, optimized for resource-constrained deployments, suitable for mobile and embedded AI. |
Llama 3.2 Community License |
Free (open-sourc |
Qwen Open Source LLMs
Qwen refers to the LLM family built by Alibaba Cloud. Qwen2 has generally surpassed most open source models and demonstrated competitiveness against proprietary models across a series of benchmarks targeting for language understanding, language generation, multilingual capability, coding, mathematics, reasoning, etc.
| Model | Parameters | Context Window | Max Output Tokens | Knowledge Cutoff | Strengths & Features | License Type |
|---|---|---|---|---|---|---|
| Qwen-2.5-7B | 7 billion | Not specified | Not specified | Not specified |
Enhanced general-purpose capabilities with improved performance.
|
Apache 2.0 |
| Qwen-2.5-14B | 14 billion | Not specified | Not specified | Not specified |
Higher performance for more complex tasks and reasoning scenarios.
|
Apache 2.0 |
| Qwen-2.5-32B | 32 billion | Not specified | Not specified | Not specified |
Advanced model suitable for highly complex tasks, reasoning, and language generation.
|
Apache 2.0 |
| Qwen-2.5-72B | 72 billion | Not specified | Not specified | Not specified |
Large-scale model offering extensive capabilities in deep understanding and generation tasks.
|
Apache 2.0 |
| Qwen-2.5-7B-Instruct-1M | 7 billion | Up to 1 million tokens | Not specified | Not specified |
Instruction-tuned, supports extended contexts, optimized for tasks requiring long context understanding.
|
Apache 2.0 |
| Qwen-2.5-14B-Instruct-1M | 14 billion | Up to 1 million tokens | Not specified | Not specified |
Larger instruction-tuned model designed for complex tasks requiring extensive context.
|
Apache 2.0 |
| Qwen-2.5-Coder-32B-Instruct | 32 billion | Not specified | Not specified | Not specified |
Optimized specifically for coding tasks, demonstrating state-of-the-art programming capabilities.
|
Apache 2.0 |
| Qwen-2-VL-Instruct-7B | 7 billion | Not specified | Not specified | Not specified | Multimodal model with vision-language capabilities, optimized for instruction-following tasks. | Apache 2.0 |
Mistral AI Open Source LLMs
Mistral AI has positioned itself as a leading provider in the AI ecosystem, catering to both enterprise and community-driven use cases.
| Model | Parameters | Context Window | Max Output Tokens | Knowledge Cutoff | Strengths & Features | Cost |
|---|---|---|---|---|---|---|
| Mistral Small (v3.1) | 24 billion | 131,000 tokens | Not specified | Mar 2025 |
Leader in small-model category; strong in text and image understanding.
|
Free (open-source) |
| Pixtral (12B) | 12 billion | 131,000 tokens | Not specified | Sep 2024 |
Mid-sized multimodal model optimized for efficient text and image processing.
|
Free (open-source) |
| Mistral Nemo | Not publicly disclosed | 131,000 tokens | Not specified | Jul 2024 |
Robust multilingual capabilities supporting extensive international languages.
|
Free (open-source) |
| Codestral Mamba | Not publicly disclosed | 256,000 tokens | Not specified | Jul 2024 |
Specialized Mamba architecture for rapid inference and efficient code generation.
|
Free (open-source) |
| Mathstral | Not publicly disclosed | 32,000 tokens | Not specified | Jul 2024 | Specialized model optimized for mathematical reasoning and computational problem-solving. | Free (open-source) |
Best LLMs for coding & software development
| Model | Company | Parameters | Context Window | Knowledge Cutoff | Key Strengths & Features | Cost (per m tokens Input/Output) |
|---|---|---|---|---|---|---|
| Claude 3.7 Sonnet | Anthropic | ~175 billion | 200,000 tokens | Oct 2024 |
Hybrid reasoning, deep code understanding, extended reasoning ability, excels in complex programming tasks.
|
$3.00 / $15.00 |
| GPT-4o | OpenAI | ~1.8 trillion | 128,000 tokens | Sep 2023 |
Versatile coding capabilities, multimodal, efficient structured outputs, fine-tuned coding instruction-following.
|
$2.50 / $10.00 |
| Gemini 2.0 Pro | Not publicly disclosed | ~2 million tokens | June 2024 |
Outstanding coding and debugging capabilities, strong integration with tools, extensive context handling.
|
Custom (Usage-based) | |
| Codestral (v25.01) | Mistral AI | Not publicly disclosed | 256,000 tokens | Jan 2025 |
Highly specialized coding LLM optimized for fast inference, real-time coding assistance, fill-in-the-middle tasks.
|
$0.0003 / $0.0009 |
| Qwen-2.5-Coder-32B-Instruct | Alibaba | 32 billion | Not specified | Not specified |
Specifically optimized for code generation, robust multilingual coding capabilities.
|
Free (Open-source) |
| DeepSeek R1 | DeepSeek | Not publicly disclosed | 128,000 tokens | Not specified |
Mixture-of-experts architecture, specialized in code generation, mathematical and computational tasks.
|
Free (Open-source) |
| Nemotron-4 340B Instruct | NVIDIA | 340 billion | 4,096 tokens | June 2023 |
Strong synthetic data generation capabilities, excellent in coding assistance, optimized for conversational tasks.
|
Free (Open-source) |
| Llama 3.3 70B Instruct | Meta | 70 billion | 128,000 tokens | Dec 2023 | Powerful multilingual instruction-following capabilities, strong open-source community for coding integrations. | Free (Open-source) |
How do I hire a senior AI development team that knows LLMs?
You could spend the next 6-18 months planning to recruit and build an AI team that knows LLMs. Or you could engage Codingscape.
We can assemble a senior AI development team for you in 4-6 weeks. It’ll be faster to get started, more cost-efficient than internal hiring, and we’ll deliver high-quality results quickly.
Zappos, Twilio, and Veho are just a few companies that trust us to build their software and systems with a remote-first approach.
You can schedule a time to talk with us here. No hassle, no expectations, just answers.
Don't Miss
Another Update
new content is published
Cole
Cole is Codingscape's Content Marketing Strategist & Copywriter.