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Claude Sonnet 4 vs Llama 3.1 8B

Compare Anthropic and Meta (via Together AI) AI models

Anthropic
Claude Sonnet 4
vs
Meta (via Together AI)
Llama 3.1 8B

Cost Comparison (1000 input + 500 output tokens, 100 requests/day)

Claude Sonnet 4

Per Request:$0.0105
Daily:$1.05
Monthly:$31.50
Yearly:$383.25

Llama 3.1 8B

Per Request:$0.000270
Daily:$0.027
Monthly:$0.81
Yearly:$9.855

Cost Differences

$0.01023
Per Request
$1.023
Daily
$30.69
Monthly
$373.395
Yearly

Llama 3.1 8B costs less than Claude Sonnet 4

Feature Comparison

FeatureClaude Sonnet 4Llama 3.1 8B
ProviderAnthropicMeta (via Together AI)
Input Price$3.00/1M tokens$0.18/1M tokens
Output Price$15.00/1M tokens$0.18/1M tokens
Context Window200,000 tokens128,000 tokens
Max Output64,000 tokens32,768 tokens
Categorystandardefficient
Capabilities
textvisioncodereasoning
textcode
Release Date5/14/20257/23/2024

Claude Sonnet 4 vs Llama 3.1 8B: Which Should You Choose?

Choosing between Claude Sonnet 4 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 tokens94% cheaper than Claude Sonnet 4. Meanwhile, Claude Sonnet 4 offers a significantly larger context window at 200,000 tokens vs 128,000 for Llama 3.1 8B.

These models come from different providers — Anthropic and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Anthropic, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.

These models target different tiers: Claude Sonnet 4 is a standard 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 Claude Sonnet 4 provides a cost-effective option for everyday tasks.

Output costs matter too. Claude Sonnet 4 charges $15.00/1M 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: Claude Sonnet 4 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 Claude Sonnet 4 when:

  • • You need a larger context window (200,000 tokens)
  • • You need more capabilities (vision, reasoning)
  • • You need longer outputs (up to 64,000 tokens)
  • • You're already using Anthropic's API ecosystem

Choose Llama 3.1 8B when:

  • • Budget is a primary concern
  • • 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

Claude Sonnet 4 (Anthropic)

Llama 3.1 8B (Meta (via Together AI))

Start using Claude Sonnet 4 today

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Start using Llama 3.1 8B today

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Frequently Asked Questions

Which is cheaper, Claude Sonnet 4 or Llama 3.1 8B?
Llama 3.1 8B is cheaper for input tokens at $0.18 per million tokens vs $3.00 for Claude Sonnet 4 — that's 94% savings on input costs.
What is the context window difference between Claude Sonnet 4 and Llama 3.1 8B?
Claude Sonnet 4 supports 200,000 tokens while Llama 3.1 8B supports 128,000 tokens — a difference of 72,000 tokens in favor of Claude Sonnet 4.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Llama 3.1 8B is the lower-cost option, while Claude Sonnet 4 offers a larger context window (200,000 vs 128,000 tokens). Choose Llama 3.1 8B for budget sensitivity or Claude Sonnet 4 for longer context tasks.
Which model has better overall pricing for heavy usage?
At 100 requests/day with 1,000 input and 500 output tokens each, Claude Sonnet 4 costs about $31.50/month and Llama 3.1 8B costs about $0.81/month. Overall, Llama 3.1 8B has lower combined input + output rates ($0.18 in, $0.18 out) vs Claude Sonnet 4.

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