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Llama 3.3 70B Instruct vs Llama 4 Scout

Llama 3.3 70B Instruct leads the LLM Stats Score 13.8 to 7.8. Llama 3.3 70B Instruct is 1.1x cheaper per token.

Meta · Meta · Updated for 2026

Which is better?

Llama 3.3 70B Instruct leads the overall LLM Stats Score 13.8 to 7.8, ranking #241 overall.

In the 5 individual benchmarks reported for both models, Llama 3.3 70B Instruct wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, Llama 3.3 70B Instruct is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Llama 4 Scout also accepts a larger context window (10,000,000 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 Llama 3.3 70B Instruct

  • overall performance matters — it scores 13.8 and ranks #241 on LLM Stats
  • you value its reported benchmark strengths — it wins 3 of 5 exact shared results
  • cost matters — it's about 1.1x cheaper per token

Choose Llama 4 Scout

  • you process long inputs — it offers a 10,000,000 token context window
  • you want the most recent training data — it shipped Apr 2025

At a glance

The differences that matter most.

Core performance indexes
13.8
#241
7.8
#282
11.7
#250
6.6
#285
9.3
#172
0.4
#239
Cost, coverage & limits
Benchmark wins
3 of 5
2 of 5
Input price
$0.10 / M
$0.08 / M
Output price
$0.20 / M
$0.30 / M
Context window
131,072
10,000,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Llama 3.3 70B Instruct
Llama 4 Scout
17.5#193
12.8#231
14.0#131
10.2#143
14.0#114
10.2#127
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for Llama 3.3 70B Instruct · 12 for Llama 4 Scout

5 shared

Llama 3.3 70B Instruct outperforms in 3 benchmarks (MATH, MGSM, MMLU), while Llama 4 Scout is better at 2 benchmarks (GPQA, MMLU-Pro).

Llama 3.3 70B Instruct has a slight edge in benchmark performance.

Sun Sep 13 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, Llama 3.3 70B Instruct ($0.10/1M tokens) is 1.3x more expensive than Llama 4 Scout ($0.08/1M tokens).

For output processing, Llama 3.3 70B Instruct ($0.20/1M tokens) is 1.5x cheaper than Llama 4 Scout ($0.30/1M tokens).

In conclusion, Llama 4 Scout 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
Sun Sep 13 2026 • llm-stats.com
Meta
Llama 3.3 70B Instruct
Input tokens$0.10
Output tokens$0.20
Best providerDeepinfra
Meta
Llama 4 Scout
Input tokens$0.08
Output tokens$0.30
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

39.0B diff

Llama 4 Scout has 39.0B more parameters than Llama 3.3 70B Instruct, making it 55.7% larger.

Meta
Llama 3.3 70B Instruct
70.0Bparameters
Meta
Llama 4 Scout
109.0Bparameters
70.0B
Llama 3.3 70B Instruct
109.0B
Llama 4 Scout

Context Window

Maximum input and output token capacity

Llama 4 Scout accepts 10,000,000 input tokens compared to Llama 3.3 70B Instruct's 131,072 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Llama 3.3 70B Instruct is limited to 131,072 tokens.

Meta
Llama 3.3 70B Instruct
Input131,072 tokens
Output131,072 tokens
Meta
Llama 4 Scout
Input10,000,000 tokens
Output10,000,000 tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

Llama 3.3 70B Instruct

Text
Images
Audio
Video

Llama 4 Scout

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.3 70B Instruct is licensed under Llama 3.3 Community License Agreement, while Llama 4 Scout uses Llama 4 Community License Agreement.

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

Llama 3.3 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Llama 4 Scout

Llama 4 Community License Agreement

Open weights

Release Timeline

When each model was launched

Llama 3.3 70B Instruct was released on 2024-12-06, while Llama 4 Scout was released on 2025-04-05.

Llama 4 Scout is 4 months newer than Llama 3.3 70B Instruct.

Llama 3.3 70B Instruct

Dec 6, 2024

1.8 years ago

Llama 4 Scout

Apr 5, 2025

1.4 years ago

4mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Llama 3.3 70B Instruct is available from DeepInfra, Lambda, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.

Llama 3.3 70B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.32/1M
lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
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

Llama 4 Scout

deepinfra logo
Deepinfra
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
lambda logo
Lambda
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
groq logo
Groq
Input Price:Input: $0.11/1MOutput Price:Output: $0.34/1M
fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
together logo
Together
Input Price:Input: $0.18/1MOutput Price:Output: $0.59/1M
* 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 Llama 3.3 70B Instruct and Llama 4 Scout side-by-side, then vote on the output you prefer.

Llama 3.3 70B Instruct
✓ Preferred
Llama 4 Scout
Open in Playground

FAQ

Common questions about Llama 3.3 70B Instruct vs Llama 4 Scout.

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

Llama 3.3 70B Instruct leads the LLM Stats Score 13.8 to 7.8. Llama 3.3 70B Instruct is made by Meta and Llama 4 Scout is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

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

Llama 3.3 70B Instruct scores IFEval: 92.1%, MGSM: 91.1%, HumanEval: 88.4%, MBPP EvalPlus: 87.6%, MMLU: 86.0%. Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%.

Is Llama 3.3 70B Instruct cheaper than Llama 4 Scout?

Llama 4 Scout is 1.3x cheaper for input tokens. Llama 3.3 70B Instruct costs $0.10/M input and $0.20/M output via deepinfra. Llama 4 Scout costs $0.08/M input and $0.30/M output via deepinfra.

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

Llama 3.3 70B Instruct supports 131K tokens and Llama 4 Scout supports 10.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

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

Key differences include LLM Stats Score (13.8 vs 7.8), context window (131K vs 10.0M), input pricing ($0.10 vs $0.08/M), multimodal support (no vs yes), licensing (Llama 3.3 Community License Agreement vs Llama 4 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.