API cost decision in 10 seconds

NewLaguna M.1 (free) vs Trinity Mini

Pick Laguna M.1 (free) when budget is the priority.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Laguna M.1 (free) when budget is the priority.

On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $0.12 for Trinity Mini, saving $0.12 (100% lower).

Cost-first pickLaguna M.1 (free)
Context-first pickBoth models
Sample savings$0.12100%
10x traffic gap$1.2

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $1.2. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Laguna M.1 (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLaguna M.1 (free)Trinity Mini
Input-heavy / RAG5M input + 500K outputLaguna M.1 (free)$0$0.3
Balanced workload1M input + 1M outputLaguna M.1 (free)$0$0.2
Output-heavy chatbot1M input + 5M outputLaguna M.1 (free)$0$0.8
Cheaper input Laguna M.1 (free) $0 vs $0.045 / 1M

Laguna M.1 (free) is free for input tokens while Trinity Mini costs $0.04 per 1M tokens.

Cheaper output Laguna M.1 (free) $0 vs $0.15 / 1M

Laguna M.1 (free) is free for output tokens while Trinity Mini costs $0.15 per 1M tokens.

Larger context Tie 131.07K vs 131.07K

Both models report the same context window at 131.07K tokens.

Sample workload Laguna M.1 (free) $0 vs $0.12

Laguna M.1 (free) is free for the standard workload while the other model is estimated at $0.12.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Laguna M.1 (free) Calculating… Estimated API cost
Trinity Mini Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Laguna M.1 (free) has the lower input price; Laguna M.1 (free) has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Laguna M.1 (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Laguna M.1 (free) and $0.12 for Trinity Mini.

Best Fit

Choose Laguna M.1 (free) when you care most about lower input-token price, and lower output-token price.

Choose Trinity Mini when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes
  • On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $0.12 for Trinity Mini, saving $0.12 (100% lower).
  • Laguna M.1 (free) is free for the standard workload while the other model is estimated at $0.12.
  • Laguna M.1 (free) is free for input tokens while Trinity Mini costs $0.04 per 1M tokens.
  • Laguna M.1 (free) is free for output tokens while Trinity Mini costs $0.15 per 1M tokens.
  • Both models report the same context window at 131.07K tokens.
Head-to-Head Specs
FeatureNewLaguna M.1 (free)
(Poolside)
Trinity Mini
(Arcee AI)
Input Price
prompt tokens per 1M
$0$0.045
Completion Price
per 1M tokens
$0$0.15
Sample Workload Cost
1M input + 500K output
$0$0.12
Context Window131.07K131.07K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLaguna M.1 (free)On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $0.12 for Trinity Mini, saving $0.12 (100% lower).
High-volume input processingLaguna M.1 (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLaguna M.1 (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workTieA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Cheaper alternatives

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

Poolside catalog

Review all tracked Poolside models before deciding whether this matchup is the right shortlist.

Open Poolside models

Arcee AI catalog

Check other Arcee AI models with comparable pricing, context, or release timing.

Open Arcee AI models
Laguna M.1 (free)

Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 128K...

Trinity Mini

Trinity Mini is a 26B-parameter (3B active) sparse mixture-of-experts language model featuring 128 experts with 8 active per token. Engineered for efficient reasoning over long contexts (131k) with robust function...