Open-source LLM Comparison 2026 + Which GPU You Need

With 500+ open-source models available in 2026, the question is no longer "is there a good open model?" but "which one for my task, and on which GPU?" This page is a direct quick reference: a comparison table of the frontier models, what each does best, and the suggested GPU to run each on GPUBrazil.

⚡ TL;DR

For general reasoning and coding, Qwen 3 235B-A22B is the best open pick. For deep math, DeepSeek R1 (~89.3 on AIME 2025). For huge context, Llama 4 Scout (up to 10M tokens). Quantized builds fit on an RTX 4090 (24GB); the large MoE models need A100/H100, often multi-GPU.

Comparison table: best open-source LLMs of 2026

Model	Best for	Approx. size	Suggested GPU
Qwen 3 235B-A22B (Alibaba)	Best overall reasoning & coding	235B total (MoE, ~22B active)	A100/H100 multi-GPU; quantized lowers the bar
DeepSeek R1	Deep math & reasoning (~89.3 AIME 2025)	Large (MoE)	A100/H100 multi-GPU
DeepSeek V3	Strong across nearly every general benchmark	Large (MoE)	A100/H100 multi-GPU
Llama 4 Scout (Meta)	Long context (up to 10M tokens)	Mid-large	Dedicated GPU; full context needs multi-GPU
Mistral Large 3	General & multilingual	Large	A100/H100; quantized may fit on 1 GPU
GLM-4.7 (Z.ai)	Competitive general use	Large	A100/H100; quantized build for 1 GPU
Kimi K2.6	Agents & agentic coding	Large (MoE)	A100/H100 multi-GPU

Sizes are approximate and vary by variant and quantization level. For exact per-GPU pricing, see live pricing in the console.

How we'd choose

Instead of hunting for "the best model in the world," think per task:

I want a general workhorse (chat, code, analysis): start with Qwen 3. If VRAM is tight, use a quantized build.
I need rigorous math and reasoning: DeepSeek R1 is the strongest bet.
I have huge documents (codebases, contracts, books): Llama 4 Scout, for its up-to-10M-token context — see the dedicated Scout guide.
I serve many languages: Mistral Large 3 and GLM-4.7 are solid multilingual options.
I'm building tool-using agents: Kimi K2.6 is built for agentic workflows and code.

Once you've picked the model, the next decision is the GPU. Quantized mid-size models fit on a single RTX 4090 (24GB); the large MoE models at full precision need A100/H100, usually multi-GPU. For a step-by-step on that decision, see how to choose between RTX 4090, A100, H100 and Rubin.

Running any of them on GPUBrazil

Every model in the table is open-weight and can be served with vLLM on a dedicated GPU, exposing an OpenAI-compatible endpoint. The flow is the same — only the model name changes:

from openai import OpenAI

client = OpenAI(
    base_url="https://your-instance.gpubrazil.com/v1",
    api_key="your-local-key",
)

resp = client.chat.completions.create(
    model="Qwen/Qwen3-235B-A22B",  # swap for any model in the table
    messages=[{"role": "user", "content": "Hello!"}],
)
print(resp.choices[0].message.content)

Because everything runs on a GPU in Brazil, data never leaves the country (good for LGPD) and you pay per hour in reais. The RTX A4000 from R$1.80/h is a good starting point for smaller models.

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Frequently asked questions

What is the best general-purpose open-source LLM in 2026?

For general reasoning and coding, Qwen 3 235B-A22B (Alibaba) is currently the open-source benchmark. For deep math, DeepSeek R1 leads (around 89.3 on AIME 2025); DeepSeek V3 is strong across nearly every general benchmark.

Which GPU do I need to run these models?

Quantized builds of mid-size models fit on a single GPU such as the RTX 4090 (24GB). The large MoE models (Qwen 3 235B, full DeepSeek V3) typically need A100/H100, often multi-GPU. On GPUBrazil you pick the GPU by model size and pay per hour in reais.

Can I run all of these models on GPUBrazil?

Yes. They are all open-weight and can be served with vLLM or TGI on a dedicated GPU on GPUBrazil, exposing an OpenAI-compatible endpoint. Data stays in Brazil, which helps LGPD compliance.

Conclusion

There's no single "best" open-source model in 2026 — there's the best one for your task. Use Qwen 3 as a general base, DeepSeek R1 for math, Llama 4 Scout for long context, and Mistral/GLM/Kimi as needed. Pair that with the right GPU and you have a sovereign stack, predictable in reais, and independent of foreign vendors.