API model string
meta-llama/Llama-3-8b-instruct (host-dependent)Context window
8K–128K tokens (host-dependent)
Max output not published (host-capped)
- Knowledge cutoff
- Dec 2023 (est.)
- Released
- Apr 2024
- Modalities
- text
Last verified July 10, 2026 — legacy model; data describes third-party host access as Meta does not offer a first-party commercial API
Rate limits by tier
Llama 3 has no first-party hosted API from Meta. All rate limits are set by the inference host you choose — Groq, Together AI, DeepInfra, or Fireworks — and vary up to 3.8× across providers.
| Tier | Requirements | RPM | TPM | RPD | Concurrent | Notes |
|---|---|---|---|---|---|---|
| Meta first-party | Waitlist only — not an active commercial endpoint | not published | not published | not published | not published | Meta's own Llama API requires waitlist access; Llama 3 (original) is not promoted on any first-party endpoint as of July 2026 |
| Groq (third-party) | Free tier available — no credit card required | ~30 (free tier); higher on paid | not published | not published | not published | Llama 3 8B served on Groq; 70B availability varies by host; always confirm current model availability in Groq console |
| Together AI (third-party) | Pay-as-you-go — credit balance required | not published | not published | not published | not published | Context often capped at 8K for Llama 3 base models on Together AI; Llama 3 8B ~$0.10–0.20/MTok blended (per third-party trackers — confirm in your console/dashboard) |
| DeepInfra (third-party) | Pay-as-you-go | not published | not published | not published | not published | Llama 3 70B ~$0.23 in / $0.40 out per third-party trackers — confirm in your dashboard before committing; host availability for Llama 3 (original) thinning as of July 2026 |
Swipe the table sideways to see every limit column.
- 1.All rate limits are set by the inference host, not Meta. Limits vary up to 3.8× across providers and change frequently.
- 2.No Meta-native rate-limit tier system exists for Llama 3. HTTP 429 behavior mirrors the host's implementation — all OpenAI-compatible hosts return 429 with Retry-After.
- 3.Context window varies by host: often 8K for Llama 3 base, up to 128K on hosts that expose larger contexts.
- 4.Llama 3 is open weights (Apache 2.0 license) — no official Meta pricing exists. Prices are set by inference hosts and vary significantly.
- 5.Representative host prices (third-party trackers — confirm in your console/dashboard before use): Together AI Llama 3 8B ~$0.10–0.20/MTok blended; DeepInfra Llama 3 70B ~$0.23 in / $0.40 out.
- 6.No standard cross-host caching or batch discount for Llama 3. For batch discounts, consider migrating to Llama 4 Scout on Amazon Bedrock (~50% batch off).
- 7.For a reliable, calculable price, migrate to Llama 4 Scout ($0.08 in / $0.30 out on DeepInfra, verified July 10, 2026).
Limits verified against the Meta docs, July 10, 2026 — legacy model; data describes third-party host access as Meta does not offer a first-party commercial API.
meta-llama/Llama-3-8b-instruct (host-dependent) vs the alternatives
Llama 3 (legacy) compared to its live successors and peers as of July 2026.
| Aspect | meta-llama/Llama-3-8b-instruct (host-dependent) | Llama 4 Scout | Llama 3.1 |
|---|---|---|---|
| Status | Legacy — no active promotion | GA (live) | Legacy (still widely served) |
| Context window | 8K–128K (host-capped) | 10M native / 128K–1M hosted | 128K |
| Cheapest input price | ~$0.10–0.20/MTok (per third-party trackers — verify) | $0.08/MTok (DeepInfra) | ~$0.35+ (70B, verify) |
| Multimodal | Text only | Text + image | Text only |
| Active host support | Thinning — some hosts have dropped Llama 3 | Broad | Broad (but Databricks dropped 405B Feb 2026) |
| First-party rate limits | not published | not published | not published |
Swipe the table sideways to see every model.
Hitting a 429? The playbook
The exact errors you'll see
429 Too Many Requestsrate_limit_exceededRateLimitErrorWhy it happens & how to fix it
Exceeding host's per-minute RPM on the free tier (e.g., Groq free ~30 RPM)
Upgrade to a paid tier on the host or switch to a host with higher free limits. Groq paid tiers offer significantly higher RPM.
TPM cap hit on a small-context host (Llama 3 often capped at 8K context per host)
Use a host exposing larger context windows (DeepInfra or Fireworks), or migrate to Llama 4 Scout which offers 10M native context.
Shared pool exhaustion during traffic bursts
Add jitter and exponential backoff to your retry logic; spread load across multiple inference hosts using round-robin routing.
Retry strategy
Use exponential backoff with jitter and honor the Retry-After header returned by the host. All OpenAI-compatible hosts (Groq, Together, DeepInfra) return this header on 429. Formula: wait = min(2^attempt + random(0,1), 60). Cap retries at 5 attempts.
1import OpenAI from 'openai';23const client = new OpenAI({4 baseURL: 'https://api.groq.com/openai/v1', // or https://api.together.xyz/v15 apiKey: process.env.HOST_API_KEY,6});78async function callWithRetry(9 prompt: string,10 maxRetries = 511): Promise<string> {12 for (let attempt = 0; attempt < maxRetries; attempt++) {13 try {14 const response = await client.chat.completions.create({15 model: 'meta-llama/Llama-3-8b-instruct', // use host-specific alias16 messages: [{ role: 'user', content: prompt }],17 });18 return response.choices[0].message.content ?? '';19 } catch (err: any) {20 if (err?.status === 429) {21 const retryAfter = parseInt(err?.headers?.['retry-after'] ?? '0', 10);22 const jitter = Math.random();23 const wait = retryAfter > 024 ? retryAfter * 100025 : Math.min(Math.pow(2, attempt) + jitter, 60) * 1000;26 console.warn(`429 — attempt ${attempt + 1}/${maxRetries}, waiting ${wait}ms`);27 await new Promise(r => setTimeout(r, wait));28 } else {29 throw err;30 }31 }32 }33 throw new Error('Max retries exceeded after 429 responses');34}How to raise your limits
The ladder from the starter tier to enterprise — what each rung takes, and what it unlocks.
Free (Groq)
ImmediateSign up at groq.com — no credit card required
Unlocks: ~30 RPM on available Llama 3 models (8B most commonly); fastest free inference
Paid host tier
Immediate on paymentAdd credit balance ($10–$50) on Together AI, DeepInfra, or Fireworks
Unlocks: Higher RPM, more concurrent requests, 70B access where available, larger context windows
Enterprise / dedicated (host)
1–5 business daysContact Together AI, DeepInfra, or Fireworks sales for reserved capacity
Unlocks: Reserved capacity, custom rate limits, SLAs — or consider migrating to Llama 4 Scout for better host coverage and lower cost
Cut your token spend
Migrate to Llama 4 Scout
~50% cheaper input ($0.08 vs ~$0.15+), 10M native context window, multimodal supportUpdate model string to meta-llama/Llama-4-Scout-17B-16E-Instruct on DeepInfra or Fireworks. Llama 4 Scout is actively maintained with broad host coverage.
Choose the cheapest host per workload
Up to 50% cost reduction vs default host selectionDeepInfra and Fireworks offer ~$0.08–0.15 blended for Llama 4 equivalents; Groq is fastest (~446 t/s on Scout) but slightly pricier. Compare on Artificial Analysis before committing.
Use batch endpoints where available
~50% off on eligible inference (Together AI, Fireworks offer batch)Submit requests as batch jobs rather than real-time completions for non-interactive workloads like classification or summarization.
Limit context to host's exposed window
Avoids truncation errors and improves throughputLlama 3 is often capped at 8K–128K by the host. Chunk documents to fit within the host's actual limit rather than the model's theoretical maximum.
Self-host Llama 3 open weights
Zero per-token cost at scaleLlama 3 is licensed under Apache 2.0. Deploy on your own GPU infra (A100/H100) for full control. Cost breaks even vs third-party APIs at roughly $300–500/month spend depending on GPU costs.
Migrate to Llama 3.3 70B as an intermediate step
Better performance-per-dollar than Llama 3 70B on most hosts; still widely availableLlama 3.3 70B is more recently trained and better supported than original Llama 3 while keeping the same architecture. Update model string to meta-llama/Llama-3.3-70B-Instruct.
Frequently asked questions
Does Llama 3 still work in 2026?
Yes, Llama 3 is still callable on several third-party hosts including Groq and Together AI as of July 2026, but availability is thinning. Some hosts have already dropped Llama 3 in favor of newer models. For any new project, we recommend using Llama 4 Scout or Llama 3.3 70B instead.
Is Llama 3 API free?
There is no official Meta-hosted Llama 3 API. Third-party hosts like Groq offer a free tier with approximately 30 RPM on available Llama 3 models. Paid hosts like Together AI and DeepInfra charge per million tokens — prices range from ~$0.10 to $0.40/MTok depending on model size and host (per third-party trackers; confirm in your dashboard).
How do I increase Llama 3 rate limits?
Rate limits for Llama 3 are controlled by your inference host, not Meta. To get higher limits: upgrade from Groq's free tier to a paid plan, add credit balance on Together AI or DeepInfra, or contact the host's sales team for enterprise capacity. For the best long-term rate limits and pricing, migrating to Llama 4 Scout is the recommended path.
What does a 429 error mean on Llama 3?
A 429 means your application exceeded the rate limit set by your inference host (not Meta). On Groq free tier this is ~30 RPM. On other hosts, limits are not publicly published. Implement exponential backoff with jitter and honor the Retry-After header in the 429 response. See the retry playbook on this page for a complete TypeScript implementation.
Llama 3 vs Llama 4 Scout pricing: which is cheaper?
Llama 4 Scout is cheaper on virtually every host. On DeepInfra, Scout costs $0.08/MTok input vs ~$0.10–0.20/MTok for Llama 3 (per third-party trackers). Scout also offers 10M native context and multimodal support. There is no reason to choose Llama 3 over Scout for new projects started in 2026.
Can I self-host Llama 3?
Yes. Llama 3 is released under the Apache 2.0 license, which allows free commercial use and self-hosting without per-token costs. You will need GPU infrastructure (e.g., A100 or H100 nodes). At typical cloud GPU costs, self-hosting breaks even with third-party API spend at roughly $300–500/month. For newer capabilities, consider self-hosting Llama 4 Scout instead.
Should I still use Llama 3 or migrate to a newer model?
Migrate for new projects. Llama 3 is a legacy model with thinning host availability, no multimodal support, and no stable first-party pricing. Llama 4 Scout offers better performance, lower cost, and 10M native context. If you need help planning the migration and optimizing API quota usage for your stack, the RapidDev team offers free scoping calls at rapidevelopers.com/contact.
We build AI apps that don't hit rate limits
- Retry, backoff & caching built in
- Multi-provider fallback routing
- Fixed price, you own the code
30-min call. No commitment.