Llama 3.3 70B Instruct fp8 Fast
meta/llama-3-3-70b-instruct-fp8-fastPor Meta · familia: llama · lanzado 2024-12-06 · fecha de conocimiento: 2023-12
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacidades
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.
Coding42
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability2/10
Agents50
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit13/15
- Provider availability2/10
JSON / structured output45
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume15/20
Cost efficiency52
- Headline price (log-scaled)52/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Production-readiness59
- Number of independent providers10/40
- Has published per-token price20/20
- Context window ≥ 8K8/15
- 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 | $2.58 < $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 | $5.15 < $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 | $1.70 < $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 | $4.57 < $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 | $4.83 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Detalle de precios
Precio recomendado de cloudflare-ai-gateway · workers-ai/@cf/meta/llama-3.3-70b-instruct-fp8-fast
Disponible en 2 proveedores
| Proveedor | ID de modelo del proveedor | Entrada / 1M | Salida / 1M | Contexto | Lanzado |
|---|---|---|---|---|---|
| Cloudflare Workers AI cloudflare-workers-ai | @cf/meta/llama-3.3-70b-instruct-fp8-fast | $0.293 | $2.25 | 24K | 2024-12-06 |
| Cloudflare AI Gateway cloudflare-ai-gateway | workers-ai/@cf/meta/llama-3.3-70b-instruct-fp8-fast | $0.290 | $2.25 | 128K | 2025-04-03 |
Inconsistencias de datos entre proveedores
- context_window varies: 128000, 24000
- release_date varies (span 118d): 2024-12-06, 2025-04-03
Los proveedores reportan valores distintos para este modelo. Los datos clave de arriba usan un proveedor representativo; consulta la tabla para detalles por proveedor.
Frequently asked questions
How much does Llama 3.3 70B Instruct fp8 Fast cost?
Llama 3.3 70B Instruct fp8 Fast costs $0.290 per 1M input tokens and $2.25 per 1M output tokens, sourced from cloudflare-ai-gateway. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Llama 3.3 70B Instruct fp8 Fast?
Llama 3.3 70B Instruct fp8 Fast has a context window of 24K tokens, with a max output of 24K tokens per reply. This is the total combined size of prompt + completion.
Does Llama 3.3 70B Instruct fp8 Fast support tool calling?
Yes. Llama 3.3 70B Instruct fp8 Fast supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Llama 3.3 70B Instruct fp8 Fast support structured output / JSON mode?
No. Llama 3.3 70B Instruct fp8 Fast does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.
Can Llama 3.3 70B Instruct fp8 Fast accept image input?
No. Llama 3.3 70B Instruct fp8 Fast only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Llama 3.3 70B Instruct fp8 Fast open-weight?
Yes. Llama 3.3 70B Instruct fp8 Fast'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 Llama 3.3 70B Instruct fp8 Fast?
If Llama 3.3 70B Instruct fp8 Fast doesn't fit, consider Llama-3.3-70B-Instruct, Meta-Llama-3.1-8B-Instruct, Llama 4 Scout 17B 16E Instruct. 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.
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Capability lists this model is in
Última actualización:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.