Fireworks AI model

Minimax M3

MiniMax-M3 is a native multimodal model with 1M context running ~428B parameters and ~23B activated parameters. It brings native multimodality. enabling deeper semantic fusion across text, image, and video. M3 also introduces MiniMax Sparse Attention (MSA) to improve long context efficiency, achieving frontier-level performance across long-horizon agentic benchmarks, excelling in both coding and cowork.

Provider
Fireworks AI
Availability
Available
Model ID
minimax-m3
Snapshot
2026-10-07
Evaluation Verdict

MiniMax-M3 achieves 29 on the Artificial Analysis Intelligence Index v4.3.2 and 30 on Finance & Accounting, delivering high-speed reasoning at $0.25/task and 85 TPS.

Minimax M3 Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified
SWE-bench Verified
58%
StandardMiniMax AI ↗
LiveCodeBench
50.5%
ThinkingLiveCodeBench ↗
LMSYS Coding Elo
1320Elo
Coding ArenaLMSYS Arena ↗
Pricing ($ / 1M tokens)
$0.25/ $1
$0.05 cached readStandard API Pricing

What This Means in Real Software Development

  • Achieves 29 on the Artificial Analysis Intelligence Index v4.3.2.
  • Scores 30 on the Finance & Accounting Index.
  • Delivers 85 TPS throughput at an efficient $0.25 cost per task.
  • Specialized in conversational coding, documentation generation, and test synthesis.

Swarm Multi-Agent Topology

Tier 2: Documentation & Test SpecialistRole: Coder Subagent

Best Paired With: Claude Opus 5.5 or Qwen 3.8 Max

Generates comprehensive documentation and test scaffolding quickly.

Git Worktree Isolation Advantage:

Works in isolated docs/tests branches without impacting core logic.

What Developers & Practitioners Are Saying

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

Field Consensus

"A dependable and cost-effective subagent choice for documentation writing, test scaffolding, and simple code refactors."

Verified Real-World Strengths

  • Inexpensive $0.25 cost per task with 85 TPS throughput
  • Clean documentation and natural language explanations
  • Reliable API availability and low latency

Production Caveats & Gaps

  • Struggles on very complex compiler or kernel-level codebases
  • Best managed under a strong Lead planner
Benchmark Reality Check

What the benchmark tests: Evaluates multi-turn conversation, docstring generation, and basic algorithmic challenges.

Production caveat: Deploy as a documentation or test-authoring subagent rather than the primary DAG planner.

Primary Sources & Methodology Citations

Head-to-Head Frontier Comparisons: Minimax M3 vs Rivals

Standardized, side-by-side benchmark & economics comparison against peer models

Flagship Comparative Matrix
ModelRole / TierSWE-benchLiveCodeBenchLMSYS EloAIMEInput / Output
Minimax M3Fireworks AICurrent
Tier 2: Documentation & Test Specialist58%50.5%1320—$0.25 / $1
K2 Horizon 375B A23BIndependent
Compare Minimax M3 vs K2 Horizon 375B A23B →
Tier 2: MoE Systems Specialist59.8%52%1330—$0.4 / $1.6
Tier 2: Open-Weights Specialist62%54.5%1342—$0.2 / $0.8
Tier 2: Accelerated Systems Specialist58.2%53%136577%$0.5 / $1.5
Tier 2: Code Search & Discovery Specialist54.5%47%1305—$0.15 / $0.6

Minimax M3 model overview

Minimax M3 is listed in the public Swarm catalog through Fireworks AI. This page summarizes the verified catalog fields used by Swarm without claiming real-time access for every provider account.

Provider
Fireworks AI
Family
Minimax
Context window
512K tokens
Thinking support
Not supported
Availability status
Available
Catalog ID
fireworks/minimax-m3
  • Text input
  • Text output
  • Tools
  • Fine-tuning

Run Minimax M3 in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →
bash — swarm run
$swarm ctl model set --provider fireworks --model fireworks/minimax-m3

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign Minimax M3 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.
← All Fireworks AI models

Public catalog snapshot. Catalog availability is not a real-time provider status or an access guarantee.