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Meta: Llama 3.3 70B Instruct

by Meta

7.1
Quality score / 10

Overview

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

Our take

Developers building agent-style applications will find this Llama 3.3 variant particularly suited to their needs. Its support for tool and function calling, combined with reliable structured JSON outputs, makes it a pragmatic choice for automating complex workflows, such as extracting specific data points from lengthy research documents. Unlike alternatives such as Claude or ChatGPT, which often prioritise broader conversational capabilities, this model focuses on programmatic interaction, albeit with a smaller 131,072-token context window than many current models. Ideal for those who need predictable machine-readable responses and are managing costs, as its API price of $0.13 per 1M input tokens is lower than approximately 75% of comparable models. However, the lack of a free tier means it is not suitable for casual experimentation, and its text-only input limits its utility for multimodal applications.

How Meta: Llama 3.3 70B Instruct stacks up

Among the 354 chatbots & llms tools in our directory, it ranks #276 of 343 on quality (7.1/10), 10% below the 343-tool average of 7.9, and its $0.13/1M input-token rate is in the budget end — 94% cheaper than the 333-model average of $2.14/1M.

Weighing quality against cost, Meta: Llama 3.3 70B Instruct's cost-per-quality-point of $0.02 places it in the top 20% for value among chatbots & llms tools.

Meta: Llama 3.3 70B Instruct in depth

Meta: Llama 3.3 70B Instruct, built by Meta, sits in the chatbots & llms space and is a paid tool starting at $0.13/1M tokens. Our editors rate it 7.1 out of 10 based on capability, ecosystem and value. It handles a context window of 131,072 tokens.

On the feature side, Meta: Llama 3.3 70B Instruct brings 131,072-token context window, tool / function calling, structured (json) outputs and knowledge cutoff 2023-12-31. These are the capabilities that most shape day-to-day use and separate it from thinner alternatives.

Its biggest strength is low api price — $0.13 per 1m input tokens, cheaper than roughly 75% of comparable models, while the main trade-off to weigh is that no free tier — usage is billed per token. Keep both in mind when deciding whether it fits your workflow.

Meta: Llama 3.3 70B Instruct is most often chosen for research and writing. If that matches your goals, it's a strong candidate to shortlist.

Speed
Context window
131,072 tokens
Free tier
No
Updated
2026-07-29

Key features

  • 131,072-token context window
  • Tool / function calling
  • Structured (JSON) outputs
  • Knowledge cutoff 2023-12-31

Pricing

$0.13/1M tokens
Pay per token
Paid$0.13/1M tokens
API input
$0.13 / 1M tokens
API output
$0.4 / 1M tokens
See full API pricing → llmprice.app

Pros

  • +Low API price — $0.13 per 1M input tokens, cheaper than roughly 75% of comparable models
  • +Supports tool / function calling for agent-style workflows
  • +Can return structured JSON output for reliable parsing

Cons

  • No free tier — usage is billed per token
  • Context window of 131,072 tokens is smaller than most current models
  • Text-only: does not accept image input

Who should use Meta: Llama 3.3 70B Instruct

  • Anyone looking for a chatbots & llms tool from Meta.
  • Teams and individuals focused on research and writing.
  • People who value low api price — $0.13 per 1m input tokens, cheaper than roughly 75% of comparable models.
  • Workflows that need a 131,072 tokens context window.

Who should look elsewhere

  • Anyone who needs a free tier — this tool is paid only.
  • Those for whom no free tier — usage is billed per token is a dealbreaker.
  • Users who can't accept that context window of 131,072 tokens is smaller than most current models.

Best for

10 Best Meta: Llama 3.3 70B Instruct Alternatives in 2026

Meta: Llama 3.3 70B Instruct is a strong chatbots & llms tool, but it is not the only option. Whether you are after a lower price, different features or a better fit for your workflow, here are the 10 best alternatives to Meta: Llama 3.3 70B Instruct, ranked and compared.

1
ClaudeFree tier$20/mo

Anthropic

Claude is Anthropic's family of AI assistants, known for long-context reasoning, careful writing and strong coding…

+ Best-in-class long-document reasoning+ Natural, high-quality writing+ Strong safety and reliability
Read full Claude review →
2
ChatGPTFree tier$20/mo

OpenAI

ChatGPT is OpenAI's flagship conversational AI, powering hundreds of millions of weekly users across web, mobile and…

+ Most polished and widely supported ecosystem+ Excellent general reasoning and coding+ Huge third-party integration support
Read full ChatGPT review →
3
GeminiFree tier$20/mo

Google DeepMind

Gemini is Google's natively multimodal model family, deeply integrated across Search, Workspace, Android and the Pixel…

+ Massive context window+ Tight integration with Google ecosystem+ Generous free access
Read full Gemini review →
4
Qwen: Qwen3.7 FlashPaid$0.03/1M tokens

Qwen

Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding…

+ Low API price — $0.03 per 1M input tokens, cheaper than roughly 75% of comparable models+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems
Read full Qwen: Qwen3.7 Flash review →
5
Claude Opus 5 (Fast)Paid$10.00/1M tokens

Anthropic

Fast-mode variant of [Opus 5](/anthropic/claude-opus-5) - identical capabilities with higher output speed at 2x pricing…

+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Claude Opus 5 (Fast) review →
6
Claude Opus 5Paid$5.00/1M tokens

Anthropic

Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work.

+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Claude Opus 5 review →
7

Google

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development.

+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Google: Gemini 3.6 Flash (batch) review →
8

Google

Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities.

+ Low API price — $0.15 per 1M input tokens, cheaper than roughly 75% of comparable models+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems
Read full Google: Gemini 3.5 Flash Lite (batch) review →
9
Thinking Machines: InklingPaid$1.00/1M tokens

Thinkingmachines

Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters…

+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Thinking Machines: Inkling review →
10
MoonshotAI: Kimi K3Paid$3.00/1M tokens

Moonshot AI

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI.

+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full MoonshotAI: Kimi K3 review →

Meta: Llama 3.3 70B Instruct vs top alternatives

A side-by-side look at how Meta: Llama 3.3 70B Instruct stacks up against its closest rivals.

FeatureMeta: Llama 3.3 70B InstructMetaClaudeAnthropicChatGPTOpenAIGeminiGoogle DeepMind
Quality score7.1 / 109.6 / 109.5 / 109.2 / 10
Starting price$0.13/1M tokens$20/mo$20/mo$20/mo
Free tierNoYes — Free tier availableYes — Free tier availableYes — Free tier available
API input price$0.13 / 1M tokens$10 / 1M tokens$0.5 / 1M tokens$0.75 / 1M tokens
API output price$0.4 / 1M tokens$50 / 1M tokens$3 / 1M tokens$3.75 / 1M tokens
SpeedFastFastFast
Context window131,072 tokens200K tokens128K tokens1M-2M tokens
CategoriesChatbots & LLMsChatbots & LLMs, Coding, WritingChatbots & LLMs, Coding, WritingChatbots & LLMs, Coding, Writing
Key features
  • 131,072-token context window
  • Tool / function calling
  • Structured (JSON) outputs
  • Knowledge cutoff 2023-12-31
  • Industry-leading long context (200K+ tokens)
  • Artifacts for live previews
  • Strong agentic coding (Claude Code)
  • Vision and document analysis
  • Multimodal text, image and voice input
  • Advanced data analysis (code interpreter)
  • Custom GPTs and GPT Store
  • Web browsing and real-time search
  • Up to 2M token context window
  • Deep Google Workspace integration
  • Native video and audio understanding
  • Real-time Google Search grounding
Pros
  • + Low API price — $0.13 per 1M input tokens, cheaper than roughly 75% of comparable models
  • + Supports tool / function calling for agent-style workflows
  • + Can return structured JSON output for reliable parsing
  • + Best-in-class long-document reasoning
  • + Natural, high-quality writing
  • + Strong safety and reliability
  • + Most polished and widely supported ecosystem
  • + Excellent general reasoning and coding
  • + Huge third-party integration support
  • + Massive context window
  • + Tight integration with Google ecosystem
  • + Generous free access
Cons
  • No free tier — usage is billed per token
  • Context window of 131,072 tokens is smaller than most current models
  • Text-only: does not accept image input
  • No native image generation
  • Fewer consumer integrations than ChatGPT
  • Usage caps on the most capable models
  • Can be verbose and overly cautious
  • Quality can be inconsistent on edge cases
  • Privacy concerns for some users

Frequently asked questions

Q. Is Meta: Llama 3.3 70B Instruct free?

No — Meta: Llama 3.3 70B Instruct is a paid tool, starting at $0.13/1M tokens.

Q. How much does Meta: Llama 3.3 70B Instruct cost?

Meta: Llama 3.3 70B Instruct starts at $0.13/1M tokens. API usage is around $0.13 per 1M input tokens and $0.4 per 1M output tokens.

Q. What is Meta: Llama 3.3 70B Instruct best for?

Meta: Llama 3.3 70B Instruct is best suited to research and writing, within the chatbots & llms category.

Q. What are the best Meta: Llama 3.3 70B Instruct alternatives?

Popular alternatives to Meta: Llama 3.3 70B Instruct include Claude, ChatGPT, Gemini and Qwen: Qwen3.7 Flash. Each trades off price, quality and ecosystem differently.

Q. Is there a free alternative to Meta: Llama 3.3 70B Instruct?

Yes. Claude, ChatGPT, Gemini offer a free tier, making them good starting points if you want to avoid an upfront subscription.

Q. Why switch from Meta: Llama 3.3 70B Instruct?

Common reasons include pricing, specific feature gaps (No free tier — usage is billed per token; Context window of 131,072 tokens is smaller than most current models; Text-only: does not accept image input), data-privacy requirements, or simply wanting a tool that fits your stack better.

How we rate AI tools

Our quality score weighs capability on real tasks, breadth of features and integrations, pricing and value, and how actively the tool is maintained. Scores are editorial guidance, not benchmarks — always trial a tool on your own workflow before committing. Pricing and features change frequently, so verify current details on the official site.

Ready to try Meta: Llama 3.3 70B Instruct?

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