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Llama 3.3 Instruct 70B

Meta Llama Proprietary Released Dec 2024 Official website
7.3
Vibe Coding Index · #85 of 86
Quality #85/86
7.3
VCI
Price #13/88
$0.2
$/M blended

Suite radar

Intelligence Coding Agentic

Suite scores

Intelligence
General reasoning & knowledge (Intelligence Index)
9
Coding
Code generation & software tasks (Coding Index)
12
Agentic
Multi-step tool use & agentic workflows (Agentic Index)
0

TheVibeFather rankings

Llama 3.3 Instruct 70B practical agentic coding scorecard

This is our algorithmic assessment of where Llama 3.3 Instruct 70B ranks for common vibe coding and agentic engineering workflows. Every stable 0–10 score is calculated consistently from the sourced Intelligence, Coding, and Agentic signals above—never from an unsourced opinion score.

Overall VibeFather rating
0.7 /10
#85 of 86 models
Practical area

Small, well-defined code changes

Precision on scoped edits, fixes, and implementation tasks.

Developing 1.1/10
Field rank #85 / 86

UI and CSS iteration

Front-end implementation with iterative tool-driven refinement.

Developing 1.0/10
Field rank #85 / 87

Routine debugging

Diagnosing failures and turning reasoning into correct code changes.

Developing 1.1/10
Field rank #85 / 86

Repository-wide refactors

Coordinating larger edits across files while preserving intent.

Developing 0.8/10
Field rank #85 / 86

Architecture decisions

Reasoning through tradeoffs, constraints, and system-level choices.

Developing 0.6/10
Field rank #86 / 86

Tool use and workflow execution

Planning and completing multi-step work with tools and feedback loops.

Developing 0.3/10
Field rank #87 / 87

Long autonomous coding tasks

Sustaining coherent progress across longer agentic engineering runs.

Developing 0.2/10
Field rank #86 / 86

Overall VibeFather rating

Our complete Vibe Coding Index, expressed on the same 0–10 practical scale.

Developing 0.7/10
Field rank #85 / 86
1 · Sourced signals

We start with Intelligence, Coding, Agentic benchmark evidence and preserve missing values as unverified.

2 · Practical lenses

Our code-controlled algorithm blends the native 0–100 signals by workflow and expresses the result on a stable 0–10 scale. Every required input must be present.

3 · Field ranking

Each workflow score is ranked against every model with comparable evidence, so positions update when the benchmark field changes.

The Vibe Coding Index is TheVibeFather’s code-controlled 0–100 composite for practical coding and agentic capability. Price and adoption are reported independently and never alter quality. Exact weighting remains proprietary; inputs, missing-data behavior, and per-category ranks are disclosed here. Read the benchmark methodology →

Where Llama 3.3 Instruct 70B sits

Its logo stays full-color and highlighted while the rest of the field recedes for quick comparison.

↖ Best value Premium ↗ ↙ Budget Poor value ↘ 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 $0.01 $0.03 $0.1 $0.32 $1 $3.16 $10 $31.62 BLENDED COST — $ / 1M TOKENS (LOG) VIBE CODING INDEX GPT-5.6 Sol GPT-5.6 Terra Grok 4.5 GPT-5.6 Luna GLM-5.2 Qwen3.7 Max MiniMax-M3 DeepSeek V4 Flash Nemotron 3 Ultra 550B A55B Llama 3.3 Instruct 70B
Efficient frontier Alibaba Amazon Anthropic Cohere DeepSeek Google Inclusionai Meta Llama MiniMax Mistral Moonshot NVIDIA OpenAI Stepfun Upstage Xiaomi Zhipu xAI Hover, tap or focus a model for axis guides · resting dashed lines = medians 19 model(s) hidden — data not yet verified

Model benchmark FAQ

Llama 3.3 Instruct 70B for vibe coding and agentic engineering

Answers update from this model’s current sourced scores, practical rankings, and verified pricing.

What is Llama 3.3 Instruct 70B's Vibe Coding Index?

Llama 3.3 Instruct 70B has a Vibe Coding Index of 7.3/100 and is #85 of 86 in the current field. The index is TheVibeFather's stable composite for practical AI coding, combining independently sourced Intelligence, Coding, and Agentic benchmark signals. Price and adoption are compared separately and never inflate the quality score.

How does Llama 3.3 Instruct 70B rank for vibe coding?

For vibe coding, Llama 3.3 Instruct 70B's strongest practical area is Small, well-defined code changes at 1.1/10, ranking #85 of 86 models in TheVibeFather rankings.

Is Llama 3.3 Instruct 70B good for agentic coding and autonomous tasks?

Llama 3.3 Instruct 70B scores 0.3/10 for tool use and workflow execution and 0.2/10 for long autonomous coding tasks. Those categories emphasize the Agentic benchmark signal used for multi-step planning, tool calls, edits, tests, and feedback loops.

What coding benchmark scores does Llama 3.3 Instruct 70B have?

The current sourced benchmark profile for Llama 3.3 Instruct 70B is Intelligence 9/100, Coding 12/100, Agentic 0/100. TheVibeFather converts those 0–100 signals into consistent practical 0–10 workflow scores so models can be compared for real agentic engineering work.

How much does Llama 3.3 Instruct 70B cost for agentic engineering?

The current benchmark uses a 3:1 input-to-output blend of $0.2 per million blended tokens. That places it #13 of 88 by price, where a lower rank number means less expensive.

Are vibe coding, agentic coding, and agentic engineering the same?

They describe overlapping AI-assisted software workflows. Vibe coding emphasizes directing software through intent and iteration; agentic coding emphasizes a model planning and executing multi-step work with tools; agentic engineering is the broader discipline of designing, supervising, and validating those workflows. TheVibeFather benchmarks the shared capabilities behind all three terms on every model page, including Llama 3.3 Instruct 70B.