Skip to main content

Gemini Embedding 2 vs Llama 3.1 405B

Gemini Embedding 2 vs Llama 3.1 405B: Gemini Embedding 2 is cheaper for input-heavy usage ($0.20/M vs $3.50/M input tokens), while Llama 3.1 405B is better for long-context tasks (128,000 tokens).

Direct answer: choose Gemini Embedding 2 for lower token spend and choose Llama 3.1 405B when your workload needs longer context.

Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.

Google
Gemini Embedding 2
vs
Meta (via Together AI)
Llama 3.1 405B

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

Gemini Embedding 2

Per Request:$0.000300
Daily:$0.03
Monthly:$0.90
Yearly:$10.95

Llama 3.1 405B

Per Request:$0.005250
Daily:$0.525
Monthly:$15.75
Yearly:$191.625

Cost Differences

+$0.004950
Per Request
+$0.495
Daily
+$14.85
Monthly
+$180.675
Yearly

Llama 3.1 405B costs more than Gemini Embedding 2

Quick Recommendation

Winner for direct API pricing: Gemini Embedding 2. At the default workload, Gemini Embedding 2 saves about $14.85/month ($180.675/year) versus Llama 3.1 405B.

Feature Comparison

FeatureGemini Embedding 2Llama 3.1 405B
ProviderGoogleMeta (via Together AI)
Input Price$0.20/1M tokens$3.50/1M tokens
Output Price$0.20/1M tokens$3.50/1M tokens
Context Window8,192 tokens128,000 tokens
Max Output3,072 tokens32,768 tokens
Categoryembeddingflagship
Capabilities
textvisionaudiovideoembeddings
textcodereasoning
Release Date3/10/20267/23/2024

Gemini Embedding 2 vs Llama 3.1 405B: Which Should You Choose?

Choosing between Gemini Embedding 2 and Llama 3.1 405B depends on your priorities: cost efficiency, context length, or raw capability. Gemini Embedding 2 is the more affordable option at $0.20/1M input tokens94% cheaper than Llama 3.1 405B. Meanwhile, Llama 3.1 405B offers a significantly larger context window at 128,000 tokens vs 8,192 for Gemini Embedding 2.

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 Embedding 2 is a embedding model while Llama 3.1 405B is flagship. This means they're optimized for different workloads. Llama 3.1 405B targets more demanding workloads, while Gemini Embedding 2 provides a cost-effective option for everyday tasks.

Output costs matter too. Gemini Embedding 2 charges $0.20/1M output tokens vs $3.50 for Llama 3.1 405B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Gemini Embedding 2 has the edge here at $0.20/1M output tokens.

Multimodal capabilities: Gemini Embedding 2 supports vision (image inputs) while Llama 3.1 405B is text-only. If your application needs image understanding, this narrows your choice.

Best Use Cases

Choose Gemini Embedding 2 when:

  • • Budget is a primary concern
  • • You need more capabilities (vision, audio, video, embeddings)
  • • You're already using Google's API ecosystem

Choose Llama 3.1 405B when:

  • • You need a larger context window (128,000 tokens)
  • • You need longer outputs (up to 32,768 tokens)
  • • You're already using Meta (via Together AI)'s API ecosystem

Pros and Caveats at a Glance

Gemini Embedding 2

  • Input pricing: $0.20/M tokens
  • Output pricing: $0.20/M tokens
  • Context window: 8,192 tokens
  • Max output: 3,072 tokens

Watch out for

  • Smaller context window than Llama 3.1 405B

Llama 3.1 405B

  • Input pricing: $3.50/M tokens
  • Output pricing: $3.50/M tokens
  • Context window: 128,000 tokens
  • Max output: 32,768 tokens

Watch out for

  • Higher input cost than Gemini Embedding 2
  • Higher output cost than Gemini Embedding 2

Try Different Scenarios

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

Gemini Embedding 2 (Google)

Llama 3.1 405B (Meta (via Together AI))

Start using Gemini Embedding 2 today

Sign Up for Google

Start using Llama 3.1 405B today

Sign Up for Meta (via Together AI)

Frequently Asked Questions

Which is cheaper, Gemini Embedding 2 or Llama 3.1 405B?
Gemini Embedding 2 is cheaper for input tokens at $0.20 per million tokens vs $3.50 for Llama 3.1 405B — that's 94% savings on input costs.
What is the context window difference between Gemini Embedding 2 and Llama 3.1 405B?
Gemini Embedding 2 supports 8,192 tokens while Llama 3.1 405B supports 128,000 tokens — a difference of 119,808 tokens in favor of Llama 3.1 405B.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Gemini Embedding 2 is the lower-cost option, while Llama 3.1 405B offers a larger context window (128,000 vs 8,192 tokens). Choose Gemini Embedding 2 for budget sensitivity or Llama 3.1 405B 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 Embedding 2 costs about $0.90/month and Llama 3.1 405B costs about $15.75/month. Overall, Gemini Embedding 2 has lower combined input + output rates ($0.20 in, $0.20 out) vs Llama 3.1 405B.
Where can I compare Google and Meta (via Together AI) API pricing beyond this model matchup?
See the Google vs Meta (via Together AI) provider comparison page for lineup-level averages, then review each model page for exact per-token rates.

Related Comparisons

Related Articles

Learn when to pick each model, then compare live pricing scenarios.