A capable but now-outdated open-weight model undercut by its tiny context window and newer successors.
72
Coding
68
Writing
60
Research
0
Images
62
Value
15
Long Context
Use this when
Developers and researchers who need a capable open-weight model for coding, analysis, and instruction-following tasks at a mid-range price point.
Skip this if
You need to process long documents, codebases, or conversations — the 8K context window will truncate almost any real-world task requiring extended context.
Pricing
$0.51/1M in
$0.74/1M out
→0%since May 2026
Context
8k tokens
Speed
Balanced
This is the original Llama 3 70B, not the 3.1 or 3.3 variants. Llama 3.1 70B offers a 128K context window at comparable pricing and is strongly preferred. Consider this model only if you have a specific reason to pin to the original Llama 3 checkpoint.
Strong instruction-following with notably improved accuracy over Llama 2 70B
Competitive coding performance on Python and common languages, rivaling early GPT-3.5-level outputs
Open weights allow fine-tuning and self-hosting, giving flexibility unavailable with closed models
Good multilingual capability across English, German, French, Spanish, and other major languages
Weaknesses
Tiny 8K context window is severely limiting compared to competitors like Gemini 3.1 Pro (1M tokens) or Claude Sonnet 4.6 (200K tokens)
Has been superseded by Llama 3.1 and Llama 3.3 variants which offer better performance and larger context
Struggles with complex multi-step reasoning tasks compared to frontier models like GPT-5.4 or Claude Sonnet 4.6
Real-world use cases
What people actually use Llama 3 70B Instruct for.
Writing and debugging Python scripts for data processing pipelines
Summarizing short articles or reports that fit within the 8K token limit
Answering structured Q&A queries or generating formatted JSON outputs from brief inputs
How Llama 3 70B Instruct compares
The nearest models people weigh against it, and what actually separates them.
vs Muse Spark — Against Muse Spark (Meta), Llama 3 70B Instruct runs about 77% cheaper per token and gives up 128x on context. Take Llama 3 70B Instruct unless you specifically need what Muse Spark does better.
vs Claude 3.5 Sonnet — Against Claude 3.5 Sonnet (Anthropic), Llama 3 70B Instruct runs about 97% cheaper per token and gives up 24.4x on context. Take Llama 3 70B Instruct unless you specifically need what Claude 3.5 Sonnet does better.
vs Claude Fable 5 — Against Claude Fable 5 (Anthropic), Llama 3 70B Instruct runs about 98% cheaper per token, gives up 122.1x on context and answers faster. Take Llama 3 70B Instruct unless you specifically need what Claude Fable 5 does better.
Price History
Llama 3 70B Instruct pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 2026
Ready to try it?
Start using Llama 3 70B Instruct
Developers and researchers who need a capable open-weight model for coding, analysis, and instruction-following tasks at a mid-range price point.. Start free — no card required.
Meta Superintelligence Labs' first closed frontier model — a natively multimodal agentic reasoner (text, image, video, audio, PDF in) with a parallel-agent 'Contemplating mode', priced aggressively below rivals.
Verdict
Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Quality score
89%
Pricing
$1.25/1M in
$4.25/1M out
Speed
Balanced
3/5 speed
Context
1.0M tokens
v1.0 launched April 8, 2026 alongside Llama 5; v1.1 (July 9) opened the paid API; v1.2 (Aug 5) is coding-focused and powers Muse Code. Built with 'over an order of magnitude less' pretraining compute than Llama 4 Maverick. Cache hits $0.15/1M.
MultimodalAgenticValue1M context
Best for
Agentic tool-use and multimodal reasoning at aggressive pricing
Claude 3.5 Sonnet is Anthropic's mid-cycle flagship model, balancing strong reasoning, coding, and instruction-following with a 200K context window. It sits between Haiku and Opus in Anthropic's lineup, offering near-flagship quality at a lower cost than top-tier models.
Verdict
One of the best models for coding and complex instruction-following, but its premium pricing demands premium use cases.
Quality score
81%
Pricing
$6.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
200k tokens
Pricing at $6 input / $30 output per million tokens is significantly higher than GPT-4o ($2.50/$10). Best accessed via Anthropic API or Amazon Bedrock. Claude 3.5 Sonnet (October 2024 version) supersedes the June 2024 release with improved performance.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
Verdict
New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.
Coding leaderSWE-Bench Pro #1Mythos-classParallel subagentsAgenticLong contextPremiumNew
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Pricing moves, ranking shifts, and capability updates.
New ModelMar 27, 2026
Meta: Llama 3 70B Instruct — added to UseRightAI
Meta: Llama 3 70B Instruct (Meta) is now indexed. A capable but now-outdated open-weight model undercut by its tiny context window and newer successors.
Llama 3 70B Instruct costs $0.51 per million input tokens and $0.74 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $6.58 at list price, before any batch or caching discounts.
What is Llama 3 70B Instruct best for?
Llama 3 70B Instruct is best for developers and researchers who need a capable open-weight model for coding, analysis, and instruction-following tasks at a mid-range price point.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
When should I avoid Llama 3 70B Instruct?
You need to process long documents, codebases, or conversations — the 8K context window will truncate almost any real-world task requiring extended context.
What is a cheaper alternative to Llama 3 70B Instruct?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against Llama 3 70B Instruct's $0.51/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if Llama 3 70B Instruct's pricing is the thing stopping you.
What is a faster alternative to Llama 3 70B Instruct?
Muse Spark — balanced against Llama 3 70B Instruct's balanced, with 1.0M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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