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GPT-4 vs Llama 3.3 70B Instruct

Llama 3.3 70B Instruct leads the LLM Stats Score 14.3 to 3.7. Llama 3.3 70B Instruct is 187.5x cheaper per token.

OpenAI · Meta · Updated for 2026

Which is better?

Llama 3.3 70B Instruct leads the overall LLM Stats Score 14.3 to 3.7, ranking #219 overall.

In the 5 individual benchmarks reported for both models, Llama 3.3 70B Instruct wins 4; this is a narrower head-to-head signal than the composite indexes.

On price, Llama 3.3 70B Instruct is roughly 187.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Llama 3.3 70B Instruct also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-4

  • you want predictable pricing at $30.00/M input and $60.00/M output

Choose Llama 3.3 70B Instruct

  • overall performance matters — it scores 14.3 and ranks #219 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 4 of 5 exact shared results
  • cost matters — it's about 187.5x cheaper per token
  • you process long inputs — it offers a 128,000 token context window
  • you want the most recent training data — it shipped Dec 2024
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
3.7
#288
14.3
#219
3.7
#280
12.2
#230
-5.1
#242
9.4
#158
Cost, coverage & limits
Benchmark wins
1 of 5
4 of 5
Input price
$30.00 / M
$0.20 / M
Output price
$60.00 / M
$0.20 / M
Context window
32,768
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-4
Llama 3.3 70B Instruct
8.8#244
17.7#179
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for GPT-4 · 9 for Llama 3.3 70B Instruct

5 shared

GPT-4 outperforms in 1 benchmarks (MMLU), while Llama 3.3 70B Instruct is better at 4 benchmarks (GPQA, HumanEval, MATH, MGSM).

Llama 3.3 70B Instruct significantly outperforms across most benchmarks.

Sat Aug 29 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Llama 3.3 70B Instruct costs less

For input processing, GPT-4 ($30.00/1M tokens) is 150.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).

For output processing, GPT-4 ($60.00/1M tokens) is 300.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).

In conclusion, GPT-4 is more expensive than Llama 3.3 70B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Aug 29 2026 • llm-stats.com
OpenAI
GPT-4
Input tokens$30.00
Output tokens$60.00
Best providerAzure
Meta
Llama 3.3 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Llama 3.3 70B Instruct accepts 128,000 input tokens compared to GPT-4's 32,768 tokens. Llama 3.3 70B Instruct can generate longer responses up to 128,000 tokens, while GPT-4 is limited to 32,768 tokens.

OpenAI
GPT-4
Input32,768 tokens
Output32,768 tokens
Meta
Llama 3.3 70B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Aug 29 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-4 supports multimodal inputs, whereas Llama 3.3 70B Instruct does not.

GPT-4 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4

Text
Images
Audio
Video

Llama 3.3 70B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4 is licensed under a proprietary license, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.

License differences may affect how you can use these models in commercial or open-source projects.

GPT-4

Proprietary

Closed source

Llama 3.3 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Release Timeline

When each model was launched

GPT-4 was released on 2023-06-13, while Llama 3.3 70B Instruct was released on 2024-12-06.

Llama 3.3 70B Instruct is 18 months newer than GPT-4.

GPT-4

Jun 13, 2023

3.2 years ago

Llama 3.3 70B Instruct

Dec 6, 2024

1.7 years ago

1.5yr newer

Knowledge Cutoff

When training data ends

GPT-4 has a documented knowledge cutoff of 2022-12-31, while Llama 3.3 70B Instruct's cutoff date is not specified.

We can confirm GPT-4's training data extends to 2022-12-31, but cannot make a direct comparison without Llama 3.3 70B Instruct's cutoff date.

GPT-4

Dec 2022

Llama 3.3 70B Instruct

Provider Availability

GPT-4 is available from Azure, OpenAI. Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.

GPT-4

azure logo
Azure
Input Price:Input: $30.00/1MOutput Price:Output: $60.00/1M
openai logo
OpenAI
Input Price:Input: $30.00/1MOutput Price:Output: $60.00/1M

Llama 3.3 70B Instruct

lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.23/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
groq logo
Groq
Input Price:Input: $0.59/1MOutput Price:Output: $7.90/1M
sambanova logo
Sambanova
Input Price:Input: $0.60/1MOutput Price:Output: $1.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.70/1MOutput Price:Output: $0.80/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
together logo
Together
Input Price:Input: $0.88/1MOutput Price:Output: $0.88/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-4 and Llama 3.3 70B Instruct side-by-side, then vote on the output you prefer.

GPT-4
✓ Preferred
Llama 3.3 70B Instruct
Open in Playground

FAQ

Common questions about GPT-4 vs Llama 3.3 70B Instruct.

Which is better, GPT-4 or Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct leads the LLM Stats Score 14.3 to 3.7. GPT-4 is made by OpenAI and Llama 3.3 70B Instruct is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-4 compare to Llama 3.3 70B Instruct in benchmarks?

GPT-4 scores AI2 Reasoning Challenge (ARC): 96.3%, HellaSwag: 95.3%, Uniform Bar Exam: 90.0%, SAT Math: 89.0%, LSAT: 88.0%. Llama 3.3 70B Instruct scores IFEval: 92.1%, MGSM: 91.1%, HumanEval: 88.4%, MBPP EvalPlus: 87.6%, MMLU: 86.0%.

Is GPT-4 cheaper than Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct is 150.0x cheaper for input tokens. GPT-4 costs $30.00/M input and $60.00/M output via azure. Llama 3.3 70B Instruct costs $0.20/M input and $0.20/M output via lambda.

What are the context window sizes for GPT-4 and Llama 3.3 70B Instruct?

GPT-4 supports 33K tokens and Llama 3.3 70B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4 and Llama 3.3 70B Instruct?

Key differences include LLM Stats Score (3.7 vs 14.3), context window (33K vs 128K), input pricing ($30.00 vs $0.20/M), multimodal support (yes vs no), licensing (Proprietary vs Llama 3.3 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4 and Llama 3.3 70B Instruct?

GPT-4 is developed by OpenAI and Llama 3.3 70B Instruct is developed by Meta.