API cost decision in 10 seconds

Llama 3.1 70B Instruct vs Nano Banana (Gemini 2.5 Flash Image)

Pick Llama 3.1 70B Instruct when budget and context both matter.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T19:08:13Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Llama 3.1 70B Instruct when budget and context both matter.

On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $1.55 for Nano Banana (Gemini 2.5 Flash Image), saving $0.95 (61.3% lower).

Cost-first pickLlama 3.1 70B Instruct

Context-first pickLlama 3.1 70B Instruct

Sample savings$0.9561.3%

10x traffic gap$9.5

Llama 3.1 70B Instruct is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $9.5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Llama 3.1 70B Instruct stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Llama 3.1 70B Instruct	Nano Banana (Gemini 2.5 Flash Image)
Input-heavy / RAG	5M input + 500K output	Llama 3.1 70B Instruct	$2.2	$2.75
Balanced workload	1M input + 1M output	Llama 3.1 70B Instruct	$0.8	$2.8
Output-heavy chatbot	1M input + 5M output	Llama 3.1 70B Instruct	$2.4	$12.8

Cheaper input Nano Banana (Gemini 2.5 Flash Image) $0.4 vs $0.3 / 1M

Nano Banana (Gemini 2.5 Flash Image) is $0.1 cheaper per 1M input tokens (25% lower; 1.33x difference).

Cheaper output Llama 3.1 70B Instruct $0.4 vs $2.5 / 1M

Llama 3.1 70B Instruct is $2.1 cheaper per 1M output tokens (84% lower; 6.25x difference).

Larger context Llama 3.1 70B Instruct 131.07K vs 32.77K

Llama 3.1 70B Instruct has 98.3K more context (4x larger).

Sample workload Llama 3.1 70B Instruct $0.6 vs $1.55

Llama 3.1 70B Instruct is $0.95 cheaper on the standard workload (61.3% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Llama 3.1 70B Instruct Calculating… Estimated API cost

Nano Banana (Gemini 2.5 Flash Image) Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Nano Banana (Gemini 2.5 Flash Image) has the lower input price; Llama 3.1 70B Instruct has the lower output price; Llama 3.1 70B Instruct offers the larger context window. For the 1M input plus 500K output sample, Llama 3.1 70B Instruct is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.6 for Llama 3.1 70B Instruct and $1.55 for Nano Banana (Gemini 2.5 Flash Image).

Best Fit

Choose Llama 3.1 70B Instruct when you care most about lower output-token price, and larger context window.

Choose Nano Banana (Gemini 2.5 Flash Image) when you care most about lower input-token price.

Decision Notes

On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $1.55 for Nano Banana (Gemini 2.5 Flash Image), saving $0.95 (61.3% lower).
Llama 3.1 70B Instruct is $0.95 cheaper on the standard workload (61.3% lower).
Nano Banana (Gemini 2.5 Flash Image) is $0.1 cheaper per 1M input tokens (25% lower; 1.33x difference).
Llama 3.1 70B Instruct is $2.1 cheaper per 1M output tokens (84% lower; 6.25x difference).
Llama 3.1 70B Instruct has 98.3K more context (4x larger).

Head-to-Head Specs

Feature	Llama 3.1 70B Instruct (Meta)	Nano Banana (Gemini 2.5 Flash Image) (Google)
Input Price prompt tokens per 1M	$0.4	$0.3
Completion Price per 1M tokens	$0.4	$2.5
Sample Workload Cost 1M input + 500K output	$0.6	$1.55
Context Window	131.07K	32.77K
Release Date	2024-07-23	2025-10-07
Popularity	#87	#121

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Llama 3.1 70B Instruct	On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $1.55 for Nano Banana (Gemini 2.5 Flash Image), saving $0.95 (61.3% lower).
High-volume input processing	Nano Banana (Gemini 2.5 Flash Image)	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Llama 3.1 70B Instruct	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Llama 3.1 70B Instruct	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Llama 3.3 70B Instruct (free) can replace Llama 3.1 70B Instruct when lower sample workload cost matters most: $0.
Llama 3.2 3B Instruct (free) can replace Llama 3.1 70B Instruct when lower sample workload cost matters most: $0.
Llama 3.1 8B Instruct can replace Llama 3.1 70B Instruct when lower sample workload cost matters most: $0.04.
Llama 3 8B Instruct can replace Llama 3.1 70B Instruct when lower sample workload cost matters most: $0.06.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

Popular competitors

DeepSeek V4 Flash · DeepSeek · #1
Hy3 preview · Tencent · #2
Claude Opus 4.7 · Anthropic · #3
Claude Sonnet 4.6 · Anthropic · #4

Cheaper alternatives

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Provider catalogs

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Meta catalog

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Google catalog

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Open Google models

Llama 3.1 70B Instruct

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...

Nano Banana (Gemini 2.5 Flash Image)

Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation,...