Grok Build 0.1 vs Llama 3.1 8B Instruct
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on November 14, 2026· 230 models
Grok Build 0.1 is SpaceXAI’s fast coding model trained specifically for agentic software engineering workflows.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- ▲256 K tokens
- Max output
- ▲230 K
- Input, $ per 1M tokens
- $1.00
- Output, $ per 1M tokens
- $2.00
- Cache read, $ per 1M
- $0.200
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- ▲04/16/2026
- Knowledge cutoff
- —
- API id
- x-ai/grok-build-0.1
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors.
- Reasoning estimated
- Speed estimated
- ▲
- Input
- Output
- Context
- 131 K tokens
- Max output
- 16 K
- Input, $ per 1M tokens
- ▲$0.020
- Output, $ per 1M tokens
- ▲$0.040
- Cache read, $ per 1M
- —
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- 07/23/2024
- Knowledge cutoff
- 2024-07
- API id
- meta-llama/llama-3.1-8b-instruct
Which is the better API choice: Grok Build 0.1 vs Llama 3.1 8B Instruct?
- Llama 3.1 8B Instruct: cheapest input (98% less than Grok Build 0.1)
- Llama 3.1 8B Instruct: cheapest output
- Grok Build 0.1: largest context (256 K)
- Grok Build 0.1: the newest (04/16/2026)
- Grok Build 0.1: most reasoning (estimated)
- Llama 3.1 8B Instruct: the fastest (estimated)
Llama 3.1 8B Instruct costs 98% less on input and 98% less on output than Grok Build 0.1 ($0.020 / $0.040 versus $1.00 / $2.00 per million tokens). Grok Build 0.1 accepts more context (256 K). On capabilities, Grok Build 0.1 accepts images; Grok Build 0.1 has a reasoning mode.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With Llama 3.1 8B Instruct you save $22.54 a month versus Grok Build 0.1 (98% less).
The 6 cheapest for this scenario (chat, last 12 months)
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- 2Lyria 3 Clip Preview Google$0.00
- 3Qwen3.7 Flash Qwen$0.97
- 4DeepSeek V4.1 Flash DeepSeek$1.57
- 5DeepSeek V4 Flash 0731 DeepSeek$1.85
- 6Ministral 3 3B 2512 Mistral$1.90
Paste your prompt: tokens and cost per model
Rough estimate (about 4 characters per token). Nothing is sent to any server.
Cost of sending it 1,000 times (input only)
- 1Llama 3.1 8B Instruct Meta$0.002
- 2Claude Haiku 5.5 Anthropic$0.008
- 3Grok Build 0.1 xAI$0.076
- 4Claude Sonnet 5.5 Anthropic$0.152
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.2 Anthropic$0.608
- 8Claude Fable 5.1 Anthropic$0.760
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See allFrequently asked questions
Which is the better API choice: Grok Build 0.1 vs Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct costs 98% less on input and 98% less on output than Grok Build 0.1 ($0.020 / $0.040 versus $1.00 / $2.00 per million tokens). Grok Build 0.1 accepts more context (256 K). On capabilities, Grok Build 0.1 accepts images; Grok Build 0.1 has a reasoning mode.
Which is cheaper: Grok Build 0.1 and Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct is cheaper: $0.020 per million input tokens and $0.040 per million output tokens, versus $1.00 / $2.00 for Grok Build 0.1.
Which has more context: Grok Build 0.1 and Llama 3.1 8B Instruct?
Grok Build 0.1 accepts 256 K tokens of context; Llama 3.1 8B Instruct accepts 131 K.
Which is newer: Grok Build 0.1 and Llama 3.1 8B Instruct?
Grok Build 0.1 was released on 04/16/2026; Llama 3.1 8B Instruct on 07/23/2024.
What would 10,000 requests a month cost with Grok Build 0.1 and Llama 3.1 8B Instruct?
With 1,500 input and 400 output tokens per request: Grok Build 0.1: $23.00; Llama 3.1 8B Instruct: $0.46 a month, at list price.
Where do the prices come from and how often are they updated?
From the public catalogs of OpenRouter, models.dev and LiteLLM, which publish each provider's list prices. They sync once a day and the last update date is shown above the comparison.
What does price per million tokens mean?
It is what the provider charges per million tokens you send (input) or the model generates (output). A token is roughly 4 characters. Output almost always costs more than input.
Sources: OpenRouter, models.dev and LiteLLM. Prices in USD per million tokens, list price, no volume discounts. Prompt tokens are an estimate; each provider's tokenizer may differ.