Gemini Embedding 2 vs Llama 3.1 8B
Compare Google and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini Embedding 2
Llama 3.1 8B
Cost Differences
Llama 3.1 8B costs less than Gemini Embedding 2
Feature Comparison
| Feature | Gemini Embedding 2 | Llama 3.1 8B |
|---|---|---|
| Provider | Meta (via Together AI) | |
| Input Price | $0.20/1M tokens | $0.18/1M tokens |
| Output Price | $0.20/1M tokens | $0.18/1M tokens |
| Context Window | 8,192 tokens | 128,000 tokens |
| Max Output | 3,072 tokens | 32,768 tokens |
| Category | embedding | efficient |
| Capabilities | textvisionaudiovideoembeddings | textcode |
| Release Date | 3/10/2026 | 7/23/2024 |
Gemini Embedding 2 vs Llama 3.1 8B: Which Should You Choose?
Choosing between Gemini Embedding 2 and Llama 3.1 8B depends on your priorities: cost efficiency, context length, or raw capability. Llama 3.1 8B is the more affordable option at $0.18/1M input tokens — 10% cheaper than Gemini Embedding 2. Meanwhile, Llama 3.1 8B 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 8B is efficient. This means they're optimized for different workloads. Llama 3.1 8B 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 $0.18 for Llama 3.1 8B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 3.1 8B has the edge here at $0.18/1M output tokens.
Multimodal capabilities: Gemini Embedding 2 supports vision (image inputs) while Llama 3.1 8B is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Gemini Embedding 2 when:
- • You need more capabilities (vision, audio, video, embeddings)
- • You're already using Google's API ecosystem
Choose Llama 3.1 8B when:
- • Budget is a primary concern
- • 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
- • You're running high-volume, latency-sensitive workloads
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Gemini Embedding 2 (Google)
Llama 3.1 8B (Meta (via Together AI))
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