LLM Reference

Gemini 2.5 Pro vs Llama 3.1 70B Instruct

Gemini 2.5 Pro (2025) and Llama 3.1 70B Instruct (2024) are frontier reasoning models from Google DeepMind and AI at Meta. Gemini 2.5 Pro ships a 1m-token context window, while Llama 3.1 70B Instruct ships a 128k-token context window. On HumanEval, Gemini 2.5 Pro leads by 9 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Gemini 2.5 Pro fits 8x more tokens; pick it for long-context work and Llama 3.1 70B Instruct for tighter calls.

Decision scorecard

Local evidence first
SignalGemini 2.5 ProLlama 3.1 70B Instruct
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsprovider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Long context
Context window1m128k
Cheapest output$10/1M tokens$0.40/1M tokens
Provider routes4 tracked13 tracked
Shared benchmarksHumanEval leader1 shared

Decision tradeoffs

Choose Gemini 2.5 Pro when...
  • Gemini 2.5 Pro holds a shared-benchmark lead on HumanEval, ahead by 9 points.
  • Gemini 2.5 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Gemini 2.5 Pro uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
Choose Llama 3.1 70B Instruct when...
  • Llama 3.1 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
  • Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and route flexibility.
  • Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, 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 Llama 3.1 70B Instruct

Gemini 2.5 Pro

$3,500

Cheapest tracked route/tier: Google AI Studio <=200K tokens

Llama 3.1 70B Instruct

$420

Cheapest tracked route/tier: Hyperbolic AI Inference

Estimated monthly gap: $3,080. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Gemini 2.5 Pro -> Llama 3.1 70B Instruct
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Llama 3.1 70B Instruct is $9.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Llama 3.1 70B Instruct -> Gemini 2.5 Pro
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Gemini 2.5 Pro is $9.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Gemini 2.5 Pro adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2025-06-172024-07-23
Context window1m128k
Parameters70B
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryLlama 3 Community
OpennessProprietaryOpen weights
WeightsNot releasedAvailable
CodeUnknownUnknown
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2025-012023-12

Pricing and availability

Pricing attributeGemini 2.5 ProLlama 3.1 70B Instruct
Input price
<=200K tokens
$1.25/1M tokens
Standard Gemini 2.5 Pro pricing for prompts up to 200K tokens.
>200K tokens
$2.50/1M tokens
Higher Gemini 2.5 Pro tier for prompts above 200K tokens.
$0.40/1M tokens
Output price
<=200K tokens
$10/1M tokens
Standard Gemini 2.5 Pro pricing for prompts up to 200K tokens.
>200K tokens
$15/1M tokens
Higher Gemini 2.5 Pro tier for prompts above 200K tokens.
$0.40/1M tokens
Providers

Capabilities

CapabilityGemini 2.5 ProLlama 3.1 70B Instruct
VisionYesNo
MultimodalYesNo
ReasoningYesNo
JSON / Tool useYesNo
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGemini 2.5 ProLlama 3.1 70B Instruct
HumanEval93.184.1

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Last reviewed: 2026-07-11. Data sourced from public model cards and provider documentation.