Is Llama 4 Scout cheaper than GPT-5.4 nano?

Yes. Llama 4 Scout (via Together.ai) costs $0.18 input / $0.59 output per million tokens. GPT-5.4 nano costs $0.20 input / $1.25 output. Llama 4 Scout is 70% cheaper overall. For a workload of 100M input + 20M output tokens per month, Llama costs $29.60/month vs GPT-5.4 nano's $45.00/month — saving you $15.40/month.

How do I migrate from GPT-5.4 nano to Llama 4 Scout?

Sign up for Together.ai, get an API key, change the base URL to api.together.xyz, and replace the model name from 'gpt-5.4-nano' to 'meta-llama/Llama-4-Scout-17B-16E-Instruct'. Uses OpenAI-compatible API format. Migration takes 5-10 minutes.

Which is better for code generation — GPT-5.4 nano or Llama 4 Scout?

Llama 4 Scout is better for most coding tasks. It has a 1M context window (vs 400K for GPT-5.4 nano), is 70% cheaper, and has strong open-source community support. GPT-5.4 nano integrates seamlessly with OpenAI ecosystem tools but costs more.

What is the absolute cheapest AI API available?

Gemini 2.5 Flash-Lite at $0.10/$0.40 is the absolute cheapest. DeepSeek V4 Flash at $0.14/$0.28 is the cheapest with strong quality. Llama 4 Scout at $0.18/$0.59 is the cheapest open-source option. GPT-5.4 nano at $0.20/$1.25 is the cheapest from OpenAI.

🔓 OPEN SOURCE VS OPENAI

GPT-5.4 nano vs Llama 4 Scout

Cheapest OpenAI model vs best open-source alternative. Llama 4 Scout is 70% cheaper with a 1M context window. Here's everything you need to decide: pricing, performance, API compatibility, and migration difficulty.

📊 Side-by-Side Comparison

GPT-5.4 nano

OpenAI

$0.20 / $1.25

per 1M tokens (input/output)

Status✅ Active
Context Window400K tokens
API FormatOpenAI Compatible
SDKPython, Node.js, Go
Code QualityGood
Monthly Cost (100M in/20M out)$45.00

Llama 4 Scout

Meta (via Together.ai)

$0.18 / $0.59

per 1M tokens (input/output) — 70% cheaper

Status✅ Active
Context Window1M tokens
API FormatOpenAI Compatible
SDKPython, Node.js, Go
Code QualityVery Good
Monthly Cost (100M in/20M out)$29.60

💰 VALUE WINNER: Llama 4 Scout

Llama 4 Scout is 70% cheaper with 2.5x larger context

For most use cases, Llama 4 Scout offers the best value. You save $15.40/month compared to GPT-5.4 nano for the same workload. Llama has a 1M context window (vs 400K) and uses OpenAI-compatible API format via Together.ai — migration takes 5-10 minutes.

💰 Detailed Pricing Comparison

All prices are per 1 million tokens:

Model	Input Price	Output Price	Monthly Cost*	vs GPT-5.4 nano
GPT-5.4 nano	$0.20	$1.25	$45.00	—
Llama 4 Scout ✅	$0.18	$0.59	$29.60	Save 70%
DeepSeek V4 Flash ✅	$0.14	$0.28	$19.60	Save 56%
Gemini 2.5 Flash-Lite ✅	$0.10	$0.40	$18.00	Save 60%
Mistral Small 4 ✅	$0.10	$0.30	$16.00	Save 64%

* Monthly cost based on 100M input tokens + 20M output tokens per month.

🔄 How to Migrate from GPT-5.4 nano to Llama 4 Scout

The migration is trivial — Together.ai uses OpenAI-compatible API format. Here's what changes:

Sign Up for Together.ai

Create an account at api.together.xyz and generate an API key. Free tier available with generous limits.

Update Base URL

Change the API base URL from https://api.openai.com/v1 to https://api.together.xyz/v1

Change Model Name

Replace gpt-5.4-nano with meta-llama/Llama-4-Scout-17B-16E-Instruct in your code.

Test & Deploy

Make a test call, verify output quality, then deploy. Total time: 5-10 minutes.

Code Comparison

❌ Before — GPT-5.4 nano (OpenAI)

from openai import OpenAI

client = OpenAI(api_key="sk-...")
response = client.chat.completions.create(
    model="gpt-5.4-nano",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

✅ After — Llama 4 Scout (Together.ai)

from openai import OpenAI

client = OpenAI(
    api_key="your-together-key",
    base_url="https://api.together.xyz/v1"
)
response = client.chat.completions.create(
    model="meta-llama/Llama-4-Scout-17B-16E-Instruct",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

🎯 Which Should You Choose?

It depends on your use case. Here's our recommendation:

💰 Cost-Sensitive Applications

Chatbots, content generation, summarization, basic coding assistance

✅ Recommended: Llama 4 Scout (70% cheaper)

📄 Long Documents

Analyzing 400K+ token documents, legal contracts, research papers

✅ Recommended: Llama 4 Scout (1M context vs 400K)

💻 Code Generation

Writing code, debugging, code review, refactoring

⚡ Either works — test both for your language

🤖 OpenAI Ecosystem

Using OpenAI plugins, fine-tuned models, or specific OpenAI features

✅ Recommended: GPT-5.4 nano (native OpenAI)

🔒 Self-Hosting

Running models on your own infrastructure, data privacy requirements

✅ Recommended: Llama 4 Scout (open-source, self-hostable)

💸 Maximum Savings

Highest volume, budget-constrained, quality can vary

✅ Recommended: Gemini 2.5 Flash-Lite ($0.10/$0.40)

📝 The Bottom Line

If you want the cheapest option with strong quality: Switch to Llama 4 Scout via Together.ai. It's 70% cheaper, has a 1M context window (vs 400K), and uses OpenAI-compatible API format — migration takes 5-10 minutes.

If you need OpenAI ecosystem features: Stay with GPT-5.4 nano. Same API key, same SDK, no changes needed. You pay more for OpenAI integration.

If you want to self-host: Llama 4 Scout is open-source — download the weights and run on your own GPU cluster. No API costs at all.

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