Meta · Open weights

Llama 3.3 70B Wayfarer

Added Feb 20, 2025Open weights

Llama 3.3 70B Wayfarer is a fine-tuned version of Llama 3.3 70B, trained on a diverse set of creative writing and RP datasets with a focus on variety and deduplication. This model is designed to be highly creative and non-repetitive by making sure no two entries in the dataset have repeated characters or situations, which makes sure the model does not latch on to a certain personality and be capable of understanding and acting appropriately to any characters or situations.

Input: Text
Output: Text
Discovery tier: Open weights

Pricing

USD per 1M tokens

Input: $0.70
Output: $0.70

Reference prices as published by the model provider. API example

Specifications

Context window: 32.8K
Max output: —
Average output (7 days): 265 tokens; Longer than 27% of 465 models

Side by side

Llama 3.3 70B Wayfarer compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Limits
	Llama 3.3 70B WayfarerMetaThis model	GLM 5.1 TEEZ.aiRemove
Provider	Meta	Z.ai
Discovery tier	Open weights	Open weights
Added	Feb 20, 2025	Apr 20, 2026
Context window	32.77K	202.75KBest
Max output	—	65.54K
Average output	265 tokens	675 tokens
Pricing, USD per 1M tokens
Input	$0.70	$0.70Best
Output	$0.70Best	$2.50
Cache read	—	$0.18
Performance
Request success (24h)	17.8%	100.0%Best
Benchmark indexes
Intelligence Index	—	26.1
Coding Index	—	55.8
Capabilities
Reasoning	No	Yes
Tools	No	Yes
Reasoning effort	—	none, high

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Llama 3.3 70B Wayfarer
GLM 5.1 TEE

Intelligence Index

Llama 3.3 70B Wayfarer—
GLM 5.1 TEE26.1

3.8Catalog models by score55.1

Indexes

Coding Index
Composite of the coding evaluations
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 55.8

Agentic work

AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 20.3%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 3.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 964 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 1,117 Elo

Document reasoning

GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 8.4%
AA-LCRv1.1
Reasoning across long documents
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 73.7%

Reasoning and knowledge

Humanity’s Last Exam
Expert-level questions across academic fields
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 30.1%
GPQA Diamond
Graduate-level science questions
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 86.8%
IFBench
Following precise output instructions
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 76.3%

Coding

Terminal-Benchv4.0
Practical software engineering in a terminal
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 2.0%
SciCode
Scientific computing in Python
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 44.8%

Legacy evaluations

Terminal-Bench Hard
Earlier terminal task suite
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 43.2%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 97.7%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Llama 3.3 70B Wayfarer: —
- GLM 5.1 TEE: 73.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Request success (24h): 17.8%

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart

curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "LatitudeGames/Wayfarer-Large-70B-Llama-3.3",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="LatitudeGames/Wayfarer-Large-70B-Llama-3.3",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Meta

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