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Gemini 2.5 Pro vs Llama 3.3 70B

Compare Google and Meta (via Together AI) AI models

Google
Gemini 2.5 Pro
vs
Meta (via Together AI)
Llama 3.3 70B

Cost Comparison (1000 input + 500 output tokens, 100 requests/day)

Gemini 2.5 Pro

Per Request:$0.006250
Daily:$0.625
Monthly:$18.75
Yearly:$228.125

Llama 3.3 70B

Per Request:$0.001320
Daily:$0.132
Monthly:$3.96
Yearly:$48.18

Cost Differences

$0.004930
Per Request
$0.493
Daily
$14.79
Monthly
$179.945
Yearly

Llama 3.3 70B costs less than Gemini 2.5 Pro

Feature Comparison

FeatureGemini 2.5 ProLlama 3.3 70B
ProviderGoogleMeta (via Together AI)
Input Price$1.25/1M tokens$0.88/1M tokens
Output Price$10.00/1M tokens$0.88/1M tokens
Context Window2,000,000 tokens131,072 tokens
Max Output131,072 tokens4,096 tokens
Categoryflagshipstandard
Capabilities
textvisionaudiovideocode
textcode
Release Date3/25/202512/6/2024

Gemini 2.5 Pro vs Llama 3.3 70B: Which Should You Choose?

Choosing between Gemini 2.5 Pro and Llama 3.3 70B depends on your priorities: cost efficiency, context length, or raw capability. Llama 3.3 70B is the more affordable option at $0.88/1M input tokens30% cheaper than Gemini 2.5 Pro. Meanwhile, Gemini 2.5 Pro offers a significantly larger context window at 2,000,000 tokens vs 131,072 for Llama 3.3 70B.

These models come from different providers — Google and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Google, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.

These models target different tiers: Gemini 2.5 Pro is a flagship model while Llama 3.3 70B is standard. This means they're optimized for different workloads. Gemini 2.5 Pro is built for complex tasks that require deeper reasoning, while Llama 3.3 70B offers better value for routine operations.

Output costs matter too. Gemini 2.5 Pro charges $10.00/1M output tokens vs $0.88 for Llama 3.3 70B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 3.3 70B has the edge here at $0.88/1M output tokens.

Multimodal capabilities: Gemini 2.5 Pro supports vision (image inputs) while Llama 3.3 70B is text-only. If your application needs image understanding, this narrows your choice.

Best Use Cases

Choose Gemini 2.5 Pro when:

  • • You need a larger context window (2,000,000 tokens)
  • • You need more capabilities (vision, audio, video)
  • • You need longer outputs (up to 131,072 tokens)
  • • You're already using Google's API ecosystem

Choose Llama 3.3 70B when:

  • • Budget is a primary concern
  • • You're already using Meta (via Together AI)'s API ecosystem

Try Different Scenarios

Use the calculator below to see how costs change with different usage patterns

Gemini 2.5 Pro (Google)

Llama 3.3 70B (Meta (via Together AI))

Start using Gemini 2.5 Pro today

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Start using Llama 3.3 70B today

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Frequently Asked Questions

Which is cheaper, Gemini 2.5 Pro or Llama 3.3 70B?
Llama 3.3 70B is cheaper for input tokens at $0.88 per million tokens vs $1.25 for Gemini 2.5 Pro — that's 30% savings on input costs.
What is the context window difference between Gemini 2.5 Pro and Llama 3.3 70B?
Gemini 2.5 Pro supports 2,000,000 tokens while Llama 3.3 70B supports 131,072 tokens — a difference of 1,868,928 tokens in favor of Gemini 2.5 Pro.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Llama 3.3 70B is the lower-cost option, while Gemini 2.5 Pro offers a larger context window (2,000,000 vs 131,072 tokens). Choose Llama 3.3 70B for budget sensitivity or Gemini 2.5 Pro for longer context tasks.
Which model has better overall pricing for heavy usage?
At 100 requests/day with 1,000 input and 500 output tokens each, Gemini 2.5 Pro costs about $18.75/month and Llama 3.3 70B costs about $3.96/month. Overall, Llama 3.3 70B has lower combined input + output rates ($0.88 in, $0.88 out) vs Gemini 2.5 Pro.

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