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Llama 3.1 8B vs o3 Deep Research

Compare Meta (via Together AI) and OpenAI AI models

Meta (via Together AI)
Llama 3.1 8B
vs
OpenAI
o3 Deep Research

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

Llama 3.1 8B

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

o3 Deep Research

Per Request:$0.03
Daily:$3.00
Monthly:$90.00
Yearly:$1,095.00

Cost Differences

+$0.02973
Per Request
+$2.973
Daily
+$89.19
Monthly
+$1,085.145
Yearly

o3 Deep Research costs more than Llama 3.1 8B

Feature Comparison

FeatureLlama 3.1 8Bo3 Deep Research
ProviderMeta (via Together AI)OpenAI
Input Price$0.18/1M tokens$10.00/1M tokens
Output Price$0.18/1M tokens$40.00/1M tokens
Context Window128,000 tokens200,000 tokens
Max Output32,768 tokens32,768 tokens
Categoryefficientreasoning
Capabilities
textcode
textreasoningvisioncode
Release Date7/23/20246/26/2025

Llama 3.1 8B vs o3 Deep Research: Which Should You Choose?

Choosing between Llama 3.1 8B and o3 Deep Research 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 tokens98% cheaper than o3 Deep Research. Meanwhile, o3 Deep Research offers a significantly larger context window at 200,000 tokens vs 128,000 for Llama 3.1 8B.

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

These models target different tiers: Llama 3.1 8B is a efficient model while o3 Deep Research is reasoning. This means they're optimized for different workloads. o3 Deep Research targets more demanding workloads, while Llama 3.1 8B provides a cost-effective option for everyday tasks.

Output costs matter too. Llama 3.1 8B charges $0.18/1M output tokens vs $40.00 for o3 Deep Research. 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: o3 Deep Research 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 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

Choose o3 Deep Research when:

  • • You need a larger context window (200,000 tokens)
  • • You need more capabilities (reasoning, vision)
  • • You're already using OpenAI's API ecosystem

Try Different Scenarios

Use the calculator below to see how costs change with different usage patterns

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

o3 Deep Research (OpenAI)

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Frequently Asked Questions

Which is cheaper, Llama 3.1 8B or o3 Deep Research?
Llama 3.1 8B is cheaper for input tokens at $0.18 per million tokens vs $10.00 for o3 Deep Research — that's 98% savings on input costs.
What is the context window difference between Llama 3.1 8B and o3 Deep Research?
Llama 3.1 8B supports 128,000 tokens while o3 Deep Research supports 200,000 tokens — a difference of 72,000 tokens in favor of o3 Deep Research.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Llama 3.1 8B is the lower-cost option, while o3 Deep Research offers a larger context window (200,000 vs 128,000 tokens). Choose Llama 3.1 8B for budget sensitivity or o3 Deep Research 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, Llama 3.1 8B costs about $0.81/month and o3 Deep Research costs about $90.00/month. Overall, Llama 3.1 8B has lower combined input + output rates ($0.18 in, $0.18 out) vs o3 Deep Research.

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