Whisper Large v3
openai/whisper-large-v3提供： OpenAI · ファミリー: whisper · リリース 2023-11-06 · 知識カットオフ: 2023-09
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
機能一覧
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.
Coding3
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability3/10
Agents3
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit0/15
- Provider availability3/10
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-readiness56
- Number of independent providers15/40
- Has published per-token price20/20
- Context window ≥ 8K0/15
- No data inconsistencies across providers6/10
- Official model (not derivative)15/15
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. |
料金詳細
推奨料金 (提供元): evroc · openai/whisper-large-v3
最安プロバイダー: nvidia · Unknown 入力 + Unknown 出力
3 か所で利用可能
| プロバイダー | プロバイダーモデルID | 入力 / 1M | 出力 / 1M | コンテキスト | リリース日 |
|---|---|---|---|---|---|
| NEAR AI Cloud nearai | openai/whisper-large-v3 | $0.010 | Unknown | 448 | 2023-11-06 |
| Nvidia nvidia | openai/whisper-large-v3 | Unknown | Unknown | Unknown | 2023-09-01 |
| evroc evroc | openai/whisper-large-v3 | $0.002 | $0.002 | 448 | 2024-10-01 |
プロバイダー間でデータに差異
- context_window varies: 0, 448
- release_date varies (span 396d): 2023-09-01, 2023-11-06, 2024-10-01
プロバイダーごとに本モデルの値が異なります。上部の「主要数値」は代表的プロバイダーを使用しています。詳細は表をご確認ください。
Frequently asked questions
How much does Whisper Large v3 cost?
Whisper Large v3 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 Large v3?
Whisper Large v3 has a context window of 448 tokens, with a max output of 448 tokens per reply. This is the total combined size of prompt + completion.
Does Whisper Large v3 support tool calling?
No. Whisper Large v3 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Whisper Large v3 support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Whisper Large v3 in our data source. Verify with OpenAI's official documentation before relying on it in production.
Can Whisper Large v3 accept image input?
No. Whisper Large v3 only accepts audio as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Whisper Large v3 open-weight?
Yes. Whisper Large v3'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 Large v3?
If Whisper Large v3 doesn't fit, consider gpt-oss-120b, GPT-5.2, gpt-oss-20b. 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 are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More OpenAI models
- gpt-oss-120b$0.04 in / $0.16 out
- GPT-5.2$1.75 in / $14.00 out
- gpt-oss-20b$0.03 in / $0.14 out
- GPT-5 Mini$0.25 in / $2.00 out
- GPT-5$1.25 in / $10.00 out
Capability lists this model is in
最終更新：
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.