Gemma 7B Instruct vs Llama 3 70B Instruct
Gemma 7B Instruct (2024) and Llama 3 70B Instruct (2024) are compact production models from Google DeepMind and AI at Meta. Gemma 7B Instruct ships a 8K-token context window, while Llama 3 70B Instruct ships a 8K-token context window. On HumanEval, Llama 3 70B Instruct leads by 2.5 pts. On pricing, Gemma 7B Instruct costs $0.05/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemma 7B Instruct is ~700% cheaper at $0.05/1M; pay for Llama 3 70B Instruct only for provider fit.
Specs
| Released | 2024-02-21 | 2024-04-18 |
| Context window | 8K | 8K |
| Parameters | 7B | 70B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2023-04 | - |
Pricing and availability
| Gemma 7B Instruct | Llama 3 70B Instruct | |
|---|---|---|
| Input price | $0.05/1M tokens | $0.4/1M tokens |
| Output price | $0.25/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Gemma 7B Instruct | Llama 3 70B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemma 7B Instruct | Llama 3 70B Instruct |
|---|---|---|
| HumanEval | 70.1 | 72.6 |
| Instruction-Following Evaluation | 42.6 | 77.8 |
| Massive Multitask Language Understanding | 75.3 | 82.0 |
Deep dive
On shared benchmark coverage, HumanEval has Gemma 7B Instruct at 70.1 and Llama 3 70B Instruct at 72.6, with Llama 3 70B Instruct ahead by 2.5 points; Instruction-Following Evaluation has Gemma 7B Instruct at 42.6 and Llama 3 70B Instruct at 77.8, with Llama 3 70B Instruct ahead by 35.2 points; Massive Multitask Language Understanding has Gemma 7B Instruct at 75.3 and Llama 3 70B Instruct at 82, with Llama 3 70B Instruct ahead by 6.7 points. The largest visible gap is 35.2 points on Instruction-Following Evaluation, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Gemma 7B Instruct lists $0.05/1M input and $0.25/1M output tokens, while Llama 3 70B Instruct lists $0.4/1M input and $0.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 7B Instruct lower by about $0.29 per million blended tokens. Availability is 8 providers versus 18, so concentration risk also matters.
Choose Gemma 7B Instruct when provider fit and lower input-token cost are central to the workload. Choose Llama 3 70B Instruct when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemma 7B Instruct or Llama 3 70B Instruct?
Gemma 7B Instruct supports 8K tokens, while Llama 3 70B Instruct supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemma 7B Instruct or Llama 3 70B Instruct?
Gemma 7B Instruct is cheaper on tracked token pricing. Gemma 7B Instruct costs $0.05/1M input and $0.25/1M output tokens. Llama 3 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 7B Instruct or Llama 3 70B Instruct open source?
Gemma 7B Instruct is listed under Open Source. Llama 3 70B Instruct is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Gemma 7B Instruct or Llama 3 70B Instruct?
Both Gemma 7B Instruct and Llama 3 70B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Gemma 7B Instruct and Llama 3 70B Instruct?
Gemma 7B Instruct is available on NVIDIA NIM, Fireworks AI, Together AI, GCP Vertex AI, and Cloudflare Workers AI. Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 7B Instruct over Llama 3 70B Instruct?
Gemma 7B Instruct is ~700% cheaper at $0.05/1M; pay for Llama 3 70B Instruct only for provider fit. If your workload also depends on provider fit, start with Gemma 7B Instruct; if it depends on provider fit, run the same evaluation with Llama 3 70B Instruct.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.