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Abliterated Model Large V2 API Pricing

1 providerabliteration/abliterated-model-large-v2Compare
Input / output
$3.00 / $5.00 per 1M tokens
Cache read
$0.30 / 1M
Context
1M tokens
Max output
1000K tokens

As of October 31, 2026, Abliterated Model Large V2 costs $3.00 per 1M input tokens and $5.00 per 1M output tokens on Abliteration, with cache reads at $0.30 per 1M tokens. It has a 1,000,000-token context window and returns up to 999,990 tokens per response.

Prices updated Checked

Abliterated Model Large V2 pricing by provider

1 listing across 1 provider. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.

Abliterated Model Large V2 prices by provider in US dollars, token prices per 1M tokens, as of October 31, 2026. Source: LiteLLM model price file.
ProviderModel name in LiteLLMInputOutputCache readContext
Abliterationabliteration/abliterated-model-large-v2$3.00$5.00$0.301M

What Abliterated Model Large V2 costs in practice

1,000 requests with 2,000 input and 500 output tokens each

Abliteration$8.50

100 long-document requests with 100,000 input and 2,000 output tokens each

Abliteration$31.00

Abliterated Model Large V2 cost calculator

At Abliteration's price ($3.00 input, $5.00 output per 1M tokens), 10,000 requests a day with 1,000 input and 500 output tokens each cost $55.00 a day, about $1,650 a month. Change the numbers for your workload, or compare it with other models.

Per request
$0.0055
Per day
$55.00
Per month (30 days)
$1,650

Abliterated Model Large V2 features

Input: text. Output: text.

Use Abliterated Model Large V2 with LiteLLM

Call Abliterated Model Large V2 through the LiteLLM Python SDK, or put it behind the LiteLLM proxy and send OpenAI-format requests to /v1/chat/completions. LiteLLM tracks the cost of every request at these prices.

Python SDK
from litellm import completion

response = completion(
    model="abliteration/abliterated-model-large-v2",
    messages=[{"role": "user", "content": "Hello!"}],
)
Proxy config.yaml
model_list:
  - model_name: abliterated-model-large-v2
    litellm_params:
      model: abliteration/abliterated-model-large-v2
      # credentials: see the provider's LiteLLM docs page
Call the proxy
curl http://0.0.0.0:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $LITELLM_API_KEY" \
  -d '{
    "model": "abliterated-model-large-v2",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Abliterated Model Large V2 FAQ

How much does Abliterated Model Large V2 cost?

Abliterated Model Large V2 costs $3.00 per 1M input tokens and $5.00 per 1M output tokens on Abliteration, with cache reads at $0.30 per 1M tokens.

What is the context window of Abliterated Model Large V2?

Abliterated Model Large V2 has a 1,000,000-token context window and returns up to 999,990 tokens per response.

Which providers offer Abliterated Model Large V2?

Abliterated Model Large V2 is available from Abliteration through LiteLLM, using the model name abliteration/abliterated-model-large-v2.

How do I call Abliterated Model Large V2 with an OpenAI-compatible API?

Use the LiteLLM Python SDK with model="abliteration/abliterated-model-large-v2", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/chat/completions from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.

What features does Abliterated Model Large V2 support?

Abliterated Model Large V2 supports function calling, structured output, reasoning and prompt caching. It does not support image input.

When did LiteLLM add Abliterated Model Large V2?

Abliterated Model Large V2 was added to LiteLLM's model price file on October 30, 2026.

Sources

Prices come from LiteLLM's open-source model_prices_and_context_window.json, which LiteLLM uses to calculate the cost of every request. Maintainers update it from each provider's published pricing, and this page is usually rebuilt within 20 minutes of every change. Provider pricing pages:

LiteLLM docs: Abliteration.

Provider pages: Abliteration.