Whisper 3 Large
evroc/whisper-large-v3Par evroc · famille: whisper · sorti 2024-10-01
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Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacités
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding1
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability1/10
Agents1
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit0/15
- Provider availability1/10
JSON / structured output20
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control0/10
- Price-friendly for high-volume20/20
Cost efficiency95
- Headline price (log-scaled)95/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Production-readiness35
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K0/15
- No data inconsistencies across providers10/10
- Official model (not derivative)0/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.01 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.03 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | < $0.01 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.02 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.03 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Détail des tarifs
Tarif recommandé de evroc · openai/whisper-large-v3
Disponible chez 1 fournisseurs
| Fournisseur | ID modèle fournisseur | Entrée / 1M | Sortie / 1M | Contexte | Publié le |
|---|---|---|---|---|---|
| evroc evroc | openai/whisper-large-v3 | $0.002 | $0.002 | 448 | 2024-10-01 |
Frequently asked questions
How much does Whisper 3 Large cost?
Whisper 3 Large costs $0.002 per 1M input tokens and $0.002 per 1M output tokens, sourced from evroc. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Whisper 3 Large?
Whisper 3 Large has a context window of 448 tokens, with a max output of 4K tokens per reply. This is the total combined size of prompt + completion.
Does Whisper 3 Large support tool calling?
No. Whisper 3 Large does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Whisper 3 Large support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Whisper 3 Large in our data source. Verify with evroc's official documentation before relying on it in production.
Can Whisper 3 Large accept image input?
No. Whisper 3 Large only accepts audio as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Whisper 3 Large open-weight?
Yes. Whisper 3 Large's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Whisper 3 Large?
If Whisper 3 Large doesn't fit, consider KB Whisper, E5 Multi-Lingual Large Embeddings 0.6B. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More evroc models
- KB Whisper$0.00 in / $0.00 out
- E5 Multi-Lingual Large Embeddings 0.6B$0.12 in / $0.12 out
Capability lists this model is in
Dernière mise à jour :
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.