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GPT-5.3 Codex vs Llama 3.1 8B

Compare OpenAI and Meta (via Together AI) AI models

OpenAI
GPT-5.3 Codex
vs
Meta (via Together AI)
Llama 3.1 8B

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

GPT-5.3 Codex

Per Request:$0.008750
Daily:$0.875
Monthly:$26.25
Yearly:$319.375

Llama 3.1 8B

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

Cost Differences

$0.008480
Per Request
$0.848
Daily
$25.44
Monthly
$309.52
Yearly

Llama 3.1 8B costs less than GPT-5.3 Codex

Feature Comparison

FeatureGPT-5.3 CodexLlama 3.1 8B
ProviderOpenAIMeta (via Together AI)
Input Price$1.75/1M tokens$0.18/1M tokens
Output Price$14.00/1M tokens$0.18/1M tokens
Context Window256,000 tokens128,000 tokens
Max Output32,768 tokens32,768 tokens
Categorycodingefficient
Capabilities
textcode
textcode
Release Date3/1/20267/23/2024

GPT-5.3 Codex vs Llama 3.1 8B: Which Should You Choose?

Choosing between GPT-5.3 Codex 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 tokens90% cheaper than GPT-5.3 Codex. Meanwhile, GPT-5.3 Codex offers a significantly larger context window at 256,000 tokens vs 128,000 for Llama 3.1 8B.

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

These models target different tiers: GPT-5.3 Codex is a coding 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 GPT-5.3 Codex provides a cost-effective option for everyday tasks.

Output costs matter too. GPT-5.3 Codex charges $14.00/1M 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.

Best Use Cases

Choose GPT-5.3 Codex when:

  • • You need a larger context window (256,000 tokens)
  • • You're already using OpenAI'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

GPT-5.3 Codex (OpenAI)

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

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Start using Llama 3.1 8B today

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Frequently Asked Questions

Which is cheaper, GPT-5.3 Codex or Llama 3.1 8B?
Llama 3.1 8B is cheaper for input tokens at $0.18 per million tokens vs $1.75 for GPT-5.3 Codex — that's 90% savings on input costs.
What is the context window difference between GPT-5.3 Codex and Llama 3.1 8B?
GPT-5.3 Codex supports 256,000 tokens while Llama 3.1 8B supports 128,000 tokens — a difference of 128,000 tokens in favor of GPT-5.3 Codex.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Llama 3.1 8B is the lower-cost option, while GPT-5.3 Codex offers a larger context window (256,000 vs 128,000 tokens). Choose Llama 3.1 8B for budget sensitivity or GPT-5.3 Codex 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, GPT-5.3 Codex costs about $26.25/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 GPT-5.3 Codex.

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