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Llama 3.3 70B

#10 on Kyma

Llama 3.3 70B is a strong, cost-effective text-only model suited for general-purpose chat, code generation, and tool use. Reach for it when you need a reliable open-weight baseline that balances capability and throughput without premium pricing.

Modalities

Text → Text

Input

$0.135 /1M

Output

$0.432 /1M

Cached input

$0.0135 /1M90% off

Context

128K

Speed

medium

Performance

Live production data from real requests on Kyma — not synthetic benchmarks.

Rank

#10

of 87 active models

Tokens served

70.9M

all-time

Success rate

99.5%

last 7 days

Median throughput190 tok/s
Total requests24,548
Platform share3.0%
Tokens · last 15 daysJul 19 → Aug 2

Top apps using this model

1Node.js App8.8M tok
2OpenClaw231.1K tok

Public apps sending the most traffic to this model — a signal of what real workloads it fits.

Pricing

Pay per token. Cached input is billed at 10% of the input rate.

$0.135 /1M input$0.432 /1M output
Hobby10 req/day · 2K in / 500 out
~$0.15/mo
Production1,000 req/day · 2K in / 500 out
~$14.58/mo
Scale20,000 req/day · 2K in / 500 out
~$292/mo
+ Estimate your workload
1,000
2,000
500
30%

Estimated monthly cost

$12.39

$0.4131 / day on Llama 3.3 70B

Same workload on:

Llama 4 Maverick$32.40+161%
Muse Spark 1.1$187+1412%

Estimates use list pricing with cached input billed at the 90%-discount rate. Actual bills depend on real token counts — every response includes its exact cost.

When to use Llama 3.3 70B

Updated 2026-07-29

Where this model earns its cost — and where it doesn't.

Meta's 70B parameter model handles text-only workloads with a 128k context window and an 8192 token output limit. It supports structured outputs, function calling, and reasoning workflows, making it a practical default for text generation tasks.

On Kyma, this model resolves the `balanced` alias. Requests are routed through an OpenAI-compatible gateway with automatic failover, and the platform tracks exact costs in the `usage.cost` field while reporting the active model in the `X-Kyma-Model` header.

The model operates at a medium speed tier with a median throughput of 234 tokens per second. It does not support vision or multimodal inputs, and outputs are strictly capped at 8192 tokens.

General Chat Applications

Handles conversational workloads with reliable context retention across 128k tokens.

Code Generation And Review

Writes and debugs code while supporting structured outputs for IDE integrations.

Tool-Driven Agent Workflows

Executes function calls and reasoning steps reliably for autonomous backend tasks.

Prompt-Cached System Prompts

Reuses long system instructions efficiently since Kyma bills cached prefixes at 10% of the standard input rate.

Not ideal for: Avoid this model if your workload requires image understanding, outputs longer than 8192 tokens, or demands the lowest possible latency.

How it compares

Against the peers people actually weigh it against.

SpecLlama 3.3 70BLlama 4 MaverickMuse Spark 1.1
Input /1M$0.135$0.27$1.688
Output /1M$0.432$1.08$5.738
Context128K1M1M
ToolsYesYesYes
ReasoningYesNoYes
Speedmediumfastmedium

Quick start

Up and running in under two minutes.

  1. 1

    Create an API key

    Sign up and grab a key from the dashboard — $0.50 free credit, no card required.

    Get API key →
  2. 2

    Make your first request

    Drop in your key and send a chat completion — fully OpenAI-compatible.

    curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.3-70b",
    "messages": [
      {"role": "user", "content": "Explain prompt caching in one paragraph."}
    ]
  }'
  3. 3

    Stream responses

    Add "stream": true to receive tokens as they arrive.

    curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.3-70b",
    "stream": true,
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

FAQ

Common questions about this model.

What is the context window of Llama 3.3 70B?

Llama 3.3 70B has a 128K-token context window — roughly 188 pages of text in a single request.

How much does the Llama 3.3 70B API cost?

$0.135 per 1M input tokens and $0.432 per 1M output tokens, with cached input at $0.0135/1M — a 90% discount on repeated prompt prefixes. No subscription; you pay only for what you use.

Does Llama 3.3 70B support function calling?

Yes — Llama 3.3 70B supports tool/function calling and structured outputs (JSON mode), so it works with agent frameworks out of the box.

How do I use Llama 3.3 70B?

Kyma is OpenAI-compatible: point your SDK's base URL at https://kymaapi.com/v1, use your Kyma API key, and set the model to llama-3.3-70b. Signing up is free and includes $0.50 of credit — no card required.

Does this model support vision or file uploads?

No, it only accepts and generates text.

How does Kyma handle routing and reliability for this model?

Every request uses automatic failover to reroute traffic if a serving path degrades, and the exact model that ran is returned in the X-Kyma-Model header.

Can I use prompt caching to reduce costs?

Yes, Kyma supports caching for this model and bills repeated prompt prefixes at 10% of the standard input rate.

Start with $0.50 free credit — no card required.Create account →

More models by Meta

ModelContextInputOutput
MetaMuse Spark 1.11M$1.688$5.738
MetaLlama 4 Maverick1M$0.27$1.08