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Gemma 2 9B vs Llama 3.1 70B Instruct

Gemma 2 9B (2024) and Llama 3.1 70B Instruct (2024) are compact production models from Google DeepMind and AI at Meta. Gemma 2 9B ships a 8K-token context window, while Llama 3.1 70B Instruct ships a 128K-token context window. On HumanEval, Llama 3.1 70B Instruct leads by 25.7 pts. On pricing, Gemma 2 9B costs $0.06/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Gemma 2 9B is ~567% cheaper at $0.06/1M; pay for Llama 3.1 70B Instruct only for long-context analysis.

Decision scorecard

Local evidence first
SignalGemma 2 9BLlama 3.1 70B Instruct
Decision fitCoding, Classification, and JSON / Tool useCoding, RAG, and Long context
Context window8K128K
Cheapest output$0.18/1M tokens$0.4/1M tokens
Provider routes3 tracked11 tracked
Shared benchmarks2 rowsHumanEval leader

Decision tradeoffs

Choose Gemma 2 9B when...
  • Gemma 2 9B has the lower cheapest tracked output price at $0.18/1M tokens.
  • Local decision data tags Gemma 2 9B for Coding, Classification, and JSON / Tool use.
Choose Llama 3.1 70B Instruct when...
  • Llama 3.1 70B Instruct leads the largest shared benchmark signal on HumanEval by 25.7 points.
  • Llama 3.1 70B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Gemma 2 9B

Gemma 2 9B

$93.00

Cheapest tracked route: GCP Vertex AI

Llama 3.1 70B Instruct

$420

Cheapest tracked route: Hyperbolic AI Inference

Estimated monthly gap: $327. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Gemma 2 9B -> Llama 3.1 70B Instruct
  • Provider overlap exists on Fireworks AI; start route-level A/B tests there.
  • Llama 3.1 70B Instruct is $0.22/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Llama 3.1 70B Instruct -> Gemma 2 9B
  • Provider overlap exists on Fireworks AI; start route-level A/B tests there.
  • Gemma 2 9B is $0.22/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2024-06-272024-07-23
Context window8K128K
Parameters9B70B
Architecturedecoder onlydecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff--

Pricing and availability

Pricing attributeGemma 2 9BLlama 3.1 70B Instruct
Input price$0.06/1M tokens$0.4/1M tokens
Output price$0.18/1M tokens$0.4/1M tokens
Providers

Capabilities

CapabilityGemma 2 9BLlama 3.1 70B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsYesYes
Code executionNoNo

Benchmarks

BenchmarkGemma 2 9BLlama 3.1 70B Instruct
HumanEval58.484.1
Massive Multitask Language Understanding71.586.0

Deep dive

On shared benchmark coverage, HumanEval has Gemma 2 9B at 58.4 and Llama 3.1 70B Instruct at 84.1, with Llama 3.1 70B Instruct ahead by 25.7 points; Massive Multitask Language Understanding has Gemma 2 9B at 71.5 and Llama 3.1 70B Instruct at 86, with Llama 3.1 70B Instruct ahead by 14.5 points. The largest visible gap is 25.7 points on HumanEval, 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 2 9B lists $0.06/1M input and $0.18/1M output tokens, while Llama 3.1 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 2 9B lower by about $0.3 per million blended tokens. Availability is 3 providers versus 11, so concentration risk also matters.

Choose Gemma 2 9B when provider fit and lower input-token cost are central to the workload. Choose Llama 3.1 70B Instruct when long-context analysis, larger context windows, 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 2 9B or Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct supports 128K tokens, while Gemma 2 9B 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 2 9B or Llama 3.1 70B Instruct?

Gemma 2 9B is cheaper on tracked token pricing. Gemma 2 9B costs $0.06/1M input and $0.18/1M output tokens. Llama 3.1 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 2 9B or Llama 3.1 70B Instruct open source?

Gemma 2 9B is listed under Open Source. Llama 3.1 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 2 9B or Llama 3.1 70B Instruct?

Both Gemma 2 9B and Llama 3.1 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 2 9B and Llama 3.1 70B Instruct?

Gemma 2 9B is available on GCP Vertex AI, Fireworks AI, and Bitdeer AI. Llama 3.1 70B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Gemma 2 9B over Llama 3.1 70B Instruct?

Gemma 2 9B is ~567% cheaper at $0.06/1M; pay for Llama 3.1 70B Instruct only for long-context analysis. If your workload also depends on provider fit, start with Gemma 2 9B; if it depends on long-context analysis, run the same evaluation with Llama 3.1 70B Instruct.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.