Gemini Embedding 2 vs Llama 4 Scout
Gemini Embedding 2 vs Llama 4 Scout: Llama 4 Scout is cheaper for input-heavy usage ($0.08/M vs $0.20/M input tokens), while Llama 4 Scout is better for long-context tasks (10,000,000 tokens).
Direct answer: choose Llama 4 Scout for lower token spend and choose Llama 4 Scout 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.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini Embedding 2
Llama 4 Scout
Cost Differences
Llama 4 Scout costs less than Gemini Embedding 2
Quick Recommendation
Winner for direct API pricing: Llama 4 Scout. At the default workload, Llama 4 Scout saves about $0.21/month ($2.555/year) versus Gemini Embedding 2.
Feature Comparison
| Feature | Gemini Embedding 2 | Llama 4 Scout |
|---|---|---|
| Provider | Meta (via Together AI) | |
| Input Price | $0.20/1M tokens | $0.08/1M tokens |
| Output Price | $0.20/1M tokens | $0.30/1M tokens |
| Context Window | 8,192 tokens | 10,000,000 tokens |
| Max Output | 3,072 tokens | 32,768 tokens |
| Category | embedding | efficient |
| Capabilities | textvisionaudiovideoembeddings | textvisioncode |
| Release Date | 3/10/2026 | 4/5/2025 |
Gemini Embedding 2 vs Llama 4 Scout: Which Should You Choose?
Choosing between Gemini Embedding 2 and Llama 4 Scout depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Scout is the more affordable option at $0.08/1M input tokens — 60% cheaper than Gemini Embedding 2. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 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 4 Scout is efficient. This means they're optimized for different workloads. Llama 4 Scout 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 $0.30 for Llama 4 Scout. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Scout has the edge here at $0.30/1M output tokens.
Multimodal capabilities: Both models support vision (image understanding), so you can send images alongside text prompts with either option.
Best Use Cases
Choose Gemini Embedding 2 when:
- • You need more capabilities (audio, video, embeddings)
- • You're already using Google's API ecosystem
Choose Llama 4 Scout when:
- • Budget is a primary concern
- • You need a larger context window (10,000,000 tokens)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
- • You're running high-volume, latency-sensitive workloads
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
- • Higher input cost than Llama 4 Scout
- • Smaller context window than Llama 4 Scout
Llama 4 Scout
- • Input pricing: $0.08/M tokens
- • Output pricing: $0.30/M tokens
- • Context window: 10,000,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • 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 4 Scout (Meta (via Together AI))
Start using Gemini Embedding 2 today
Sign Up for Google →Start using Llama 4 Scout today
Sign Up for Meta (via Together AI) →Frequently Asked Questions
Which is cheaper, Gemini Embedding 2 or Llama 4 Scout?▼
What is the context window difference between Gemini Embedding 2 and Llama 4 Scout?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Google and Meta (via Together AI) API pricing beyond this model matchup?▼
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