OpenRouter model

Meta: Llama 3.3 70B Instruct

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...

Provider
OpenRouter
Availability
Available
Model ID
meta-llama/llama-3.3-70b-instruct
Snapshot
2026-10-07
Evaluation Verdict

Llama 3.3 70B Instruct is Meta's flagship open-weights foundation (39.8% SWE-bench, 1290 Coding Elo), providing enterprise-grade multi-language code generation with broad cloud availability.

Meta: Llama 3.3 70B Instruct Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified
SWE-bench Verified
39.8%
StandardMeta AI Technical Report ↗
LiveCodeBench
38%
StandardLiveCodeBench ↗
LMSYS Coding Elo
1290Elo
Coding ArenaLMSYS Arena ↗
AIME 2024 / 2025
34%
StandardMeta AI Technical Report ↗
Pricing ($ / 1M tokens)
$0.35/ $0.7
$0.1 cached readStandard API Pricing

What This Means in Real Software Development

  • Matches older 405B capabilities in a compact 70B footprint, offering strong efficiency.
  • Scores 39.8% on SWE-bench Verified and 38.0% on LiveCodeBench.
  • Full open weights permit local deployment, private fine-tuning, and on-premise execution.
  • Widely available across cloud providers (Together, Fireworks, Groq, OpenRouter).

Swarm Multi-Agent Topology

Tier 2: Open-Weights Enterprise SpecialistRole: Coder Subagent

Best Paired With: Claude 3.7 Sonnet as Lead Planner

Strong general code synthesis and reliable open-weights licensing for enterprise workflows.

Git Worktree Isolation Advantage:

Executes isolated feature branches inside Swarm worktrees.

What Developers & Practitioners Are Saying

Real-world field observations, production strengths, and developer consensus

Field Consensus

"Meta's flagship open-weights workhorse. Extremely reliable instruction follower with broad industry fine-tuning support."

Verified Real-World Strengths

  • High stability across diverse coding tasks and frameworks
  • Solid 39.8% on SWE-bench Verified
  • Broad provider availability across Fireworks, Together, Groq, and AWS Bedrock

Production Caveats & Gaps

  • Coding performance slightly trails specialized coding models like Qwen 2.5 Coder
  • Prone to standard conversational preamble unless strictly suppressed
Benchmark Reality Check

What the benchmark tests: Evaluates general reasoning, instruction following, and broad language comprehension.

Production caveat: Use a clear system prompt instructing the model to output only code diffs.

Primary Sources & Methodology Citations

Meta: Llama 3.3 70B Instruct model overview

Meta: Llama 3.3 70B Instruct is listed in the public Swarm catalog through OpenRouter. This page summarizes the verified catalog fields used by Swarm without claiming real-time access for every provider account.

Provider
OpenRouter
Family
OpenRouter
Context window
131.1K tokens
Thinking support
Not supported
Availability status
Available
Catalog ID
openrouter/meta-llama/llama-3.3-70b-instruct
  • Text input
  • Text output
  • Tools
  • Structured output
  • JSON

Run Meta: Llama 3.3 70B Instruct in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →
bash — swarm run
$swarm ctl model set --provider openrouter --model openrouter/meta-llama/llama-3.3-70b-instruct

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign Meta: Llama 3.3 70B Instruct to specialized system roles in ~/.swarm/config.json:

  • Primary / Planner: Orchestrates full task DAGs and multi-stage pipelines.
  • Coder Subagent: Generates code and unit tests inside private Git worktrees.
  • Finder Subagent: Performs read-only code search, symbol discovery, and mapping.
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Public catalog snapshot. Catalog availability is not a real-time provider status or an access guarantee.