LLM Reference

Gemini 3.1 Pro Preview vs Trinity-Large-Thinking

Gemini 3.1 Pro Preview (2026) and Trinity-Large-Thinking (2026) are frontier reasoning models from Google DeepMind and Arcee AI. Gemini 3.1 Pro Preview ships a 1m-token context window, while Trinity-Large-Thinking ships a 256k-token context window. On Google-Proof Q&A, Gemini 3.1 Pro Preview leads by 5.1 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Trinity-Large-Thinking is safer overall; choose Gemini 3.1 Pro Preview when coding workflow support matters.

Decision scorecard

Local evidence first
SignalGemini 3.1 Pro PreviewTrinity-Large-Thinking
Best formultimodal apps, tool-calling agents, and long-context analysisreasoning-heavy apps, tool-calling agents, and provider-routed production
Decision fitCoding, RAG, and AgentsRAG, Agents, and Long context
Context window1m256k
Cheapest output$12/1M tokens$0.85/1M tokens
Provider routes5 tracked3 tracked
Shared benchmarksGoogle-Proof Q&A leader1 rows

Decision tradeoffs

Choose Gemini 3.1 Pro Preview when...
  • Gemini 3.1 Pro Preview leads the largest shared benchmark signal on Google-Proof Q&A by 5.1 points.
  • Gemini 3.1 Pro Preview has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Gemini 3.1 Pro Preview has broader tracked provider coverage for fallback and procurement flexibility.
  • Gemini 3.1 Pro Preview uniquely exposes Vision, Multimodal, and Code execution in local model data.
  • Local decision data tags Gemini 3.1 Pro Preview for Coding, RAG, and Agents.
Choose Trinity-Large-Thinking when...
  • Trinity-Large-Thinking has the lower cheapest tracked output price at $0.85/1M tokens.
  • Trinity-Large-Thinking uniquely exposes Reasoning in local model data.
  • Local decision data tags Trinity-Large-Thinking for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Trinity-Large-Thinking

Gemini 3.1 Pro Preview

$4,600

Cheapest tracked route/tier: Google AI Studio

Trinity-Large-Thinking

$389

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $4,212. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Gemini 3.1 Pro Preview -> Trinity-Large-Thinking
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Trinity-Large-Thinking is $11.15/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
  • Trinity-Large-Thinking adds Reasoning in local capability data.
Trinity-Large-Thinking -> Gemini 3.1 Pro Preview
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Gemini 3.1 Pro Preview is $11.15/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Reasoning before moving production traffic.
  • Gemini 3.1 Pro Preview adds Vision, Multimodal, and Code execution in local capability data.

Specs

Specification
Released2026-02-192026-04-01
Context window1m256k
Parameters400B
Architecturedecoder onlySparse Mixture of Experts (MoE)
LicenseProprietaryApache 2.0
Knowledge cutoff2025-01-

Pricing and availability

Pricing attributeGemini 3.1 Pro PreviewTrinity-Large-Thinking
Input price
0-200,001t
$2/1M tokens
200,001t+
$4/1M tokens
$0.22/1M tokens
Output price
0-200,001t
$12/1M tokens
200,001t+
$18/1M tokens
$0.85/1M tokens
Providers

Capabilities

CapabilityGemini 3.1 Pro PreviewTrinity-Large-Thinking
VisionYesNo
MultimodalYesNo
ReasoningNoYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGemini 3.1 Pro PreviewTrinity-Large-Thinking
Google-Proof Q&A94.389.2

Deep dive

On shared benchmark coverage, Google-Proof Q&A has Gemini 3.1 Pro Preview at 94.3 and Trinity-Large-Thinking at 89.2, with Gemini 3.1 Pro Preview ahead by 5.1 points. The largest visible gap is 5.1 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on vision: Gemini 3.1 Pro Preview, multimodal input: Gemini 3.1 Pro Preview, reasoning mode: Trinity-Large-Thinking, and code execution: Gemini 3.1 Pro Preview. Both models share function calling, tool use, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

For cost, Gemini 3.1 Pro Preview lists tiered pricing: 0-200,001t is $2/1M input and $12/1M output; 200,001t+ is $4/1M input and $18/1M output, while Trinity-Large-Thinking lists $0.22/1M input and $0.85/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Trinity-Large-Thinking lower by about $4.59 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 5 providers versus 3, so concentration risk also matters.

Choose Gemini 3.1 Pro Preview when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Trinity-Large-Thinking when reasoning depth and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, Gemini 3.1 Pro Preview or Trinity-Large-Thinking?

Gemini 3.1 Pro Preview supports 1m tokens, while Trinity-Large-Thinking supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Gemini 3.1 Pro Preview or Trinity-Large-Thinking?

Gemini 3.1 Pro Preview lists tiered pricing: 0-200,001t is $2/1M input and $12/1M output; 200,001t+ is $4/1M input and $18/1M output. Trinity-Large-Thinking lists $0.22/1M input and $0.85/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.

Is Gemini 3.1 Pro Preview or Trinity-Large-Thinking open source?

Gemini 3.1 Pro Preview is listed under Proprietary. Trinity-Large-Thinking is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, Gemini 3.1 Pro Preview or Trinity-Large-Thinking?

Gemini 3.1 Pro Preview has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for multimodal input, Gemini 3.1 Pro Preview or Trinity-Large-Thinking?

Gemini 3.1 Pro Preview has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Gemini 3.1 Pro Preview and Trinity-Large-Thinking?

Gemini 3.1 Pro Preview is available on Google AI Studio, GCP Vertex AI, OpenRouter, Replicate API, and Vercel AI Gateway. Trinity-Large-Thinking is available on Arcee AI, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.