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LLM Models

Explore and compare the latest large language models from leading AI companies.

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179 LLM Models found

Gemini 3.1 Pro

Google

Google DeepMind's advanced reasoning model (February 2026), built for complex problem-solving with a large reasoning boost over Gemini 3 Pro. Fully multimodal with a 1M-token context window; tiered pricing doubles for prompts over 200K tokens.

Context: 1,000,000 tokens
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Gemini 3 Flash

Google

Google's fast, low-cost Gemini 3 model (December 2025), a major capability upgrade over Gemini 2.5 Flash and a default in the Gemini app. It pairs next-generation intelligence with lightning-fast latency, a ~1M-token context window, and native multimodal input.

Context: 1,048,576 tokens
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Gemini 3 Pro

Google

Google DeepMind's flagship Gemini 3 model (November 2025), a natively multimodal model with strong reasoning, coding, and agentic performance and a 1M-token context window. It became the top 'Pro' option in the Gemini app and API at launch.

Context: 1,000,000 tokens
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Gemini 3.5 Flash

Google

Google's most intelligent model for sustained frontier performance (May 2026), excelling at complex long-horizon agentic and coding tasks. Fully multimodal with a 1M-token context window, combining frontier intelligence with action.

Context: 1,000,000 tokens
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Claude Opus 4.8

Anthropic

Anthropic's premium Claude model (May 2026), delivering flagship-class reasoning and agentic coding below Fable 5 pricing. Opus 4.8 keeps Opus 4.7's $5/$25 pricing while using ~35% fewer output tokens on agentic coding, with a 1M-token context window, 128K output, adaptive thinking, and mid-conversation system messages.

Context: 1,000,000 tokens
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Claude Sonnet 5

Anthropic

Anthropic's most agentic Sonnet-class model (June 2026), narrowing the gap to Opus 4.8 on reasoning, tool use, coding, and computer use while staying far cheaper. Features a 1M-token context window with context compaction and adaptive thinking with selectable effort up to 'extra high' (xhigh). It is the default model for Claude Free and Pro plans.

Context: 1,000,000 tokens
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Claude Mythos 5

Anthropic

The unsafeguarded sibling of Claude Fable 5 - the same underlying frontier model with safety classifiers lifted, offered only in limited availability to approved Project Glasswing cybersecurity partners. In Anthropic testing, Mythos autonomously found thousands of zero-day vulnerabilities and produced 181 working Firefox exploits on a harness where Opus 4.6 produced two.

Context: 1,000,000 tokens
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Claude Fable 5

Anthropic

Anthropic's first generally available Mythos-class model (June 2026) and its most capable widely released Claude, built for the most demanding reasoning and long-horizon agentic work. Runs with always-on adaptive thinking, a 1M-token context window, and 128K output, and shares Claude Mythos 5's weights with added safety classifiers that route flagged high-risk requests to Opus 4.8.

Context: 1,000,000 tokens
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Claude Opus 4.7

Anthropic

Anthropic's most capable generally available model (April 2026), with a step-change improvement in agentic coding over Opus 4.6. Features a 1M-token context window at standard pricing, adaptive thinking, and a new tokenizer that contributes to its improved performance (and may use up to ~35% more tokens for the same text).

Context: 1,000,000 tokens
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Claude Sonnet 4.6

Anthropic

February 2026 Sonnet release offering the best combination of speed and intelligence, with a 1M-token context window at standard pricing and both extended and adaptive thinking. The recommended balanced model for most production workloads.

Context: 1,000,000 tokens
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Claude Opus 4.6

Anthropic

February 2026 Opus release that added a 1M-token context window at standard pricing and adaptive thinking. The first Opus with the dateless pinned-snapshot model ID format. Superseded by Opus 4.7.

Context: 1,000,000 tokens
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Claude Opus 4.5

Anthropic

November 2025 Opus release that dramatically cut flagship pricing (from $15/$75 to $5/$25) while improving agentic coding and reasoning. Superseded by Opus 4.6 and 4.7.

Context: 200,000 tokens
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