API model string
not applicable (no shared API exists)Context window
not published (2K-4K trained; some sources cite 8K — verify with TII before relying on this figure)
Max output not published
- Knowledge cutoff
- approximately 2023 training data
- Released
- September 6, 2023
- Modalities
- text in, text out
Last verified July 10, 2026
Rate limits by tier
Falcon 180B does not have a shared per-token API. The Falcon-180B TII License restricts 'hosting use' (serving the model to third parties) — this requires a separate license from TII, which is why no major inference host offers it. The only access paths are a dedicated SageMaker JumpStart deployment (your own VPC infrastructure) or self-hosting on your own GPU cluster.
| Tier | Requirements | RPM | TPM | RPD | Concurrent | Notes |
|---|---|---|---|---|---|---|
| Shared per-token API | n/a | n/a | n/a | n/a | n/a | DOES NOT EXIST. The Falcon-180B TII License explicitly restricts 'hosting use' — offering shared instances of Falcon 180B to third parties requires separate written permission from TII (falconllm.tii.ae). This is the reason no major inference provider (Fireworks, Together AI, DeepInfra, Replicate) serves Falcon 180B. |
| SageMaker JumpStart dedicated deployment | AWS account; one-click deploy to ml.p4de.24xlarge instances inside your own VPC | self-managed (dedicated instance) | self-managed | self-managed | self-managed | You deploy to your own AWS infrastructure via SageMaker JumpStart. You pay EC2 ml.p4de rates — this is not a per-token API. AWS Console → SageMaker → JumpStart → search 'Falcon 180B' → Deploy. Infrastructure cost: ml.p4de.24xlarge on-demand ~$32/hour → approximately $23,040/month sustained (estimated from AWS EC2 rates — verify current pricing at aws.amazon.com/ec2/pricing; reserved pricing is lower). |
| Self-host (own GPU compute) | ~640GB GPU memory at FP16 (approximately eight A100 80GB GPUs) or ~320GB at int4 (approximately eight A100 40GB GPUs); Falcon-180B TII License + Acceptable Use Policy | self-managed | self-managed | self-managed | self-managed | Weights available at huggingface.co/tiiuae/falcon-180B. License: Apache 2.0 base + TII modifications. Self-hosted inference for your own use is permitted. Serving to third parties requires separate TII license from falconllm.tii.ae. Deploy with vLLM: vllm serve tiiuae/falcon-180B --tensor-parallel-size 8 |
Swipe the table sideways to see every limit column.
- 1.Sustained dedicated inference estimated at approximately $20,000-$23,000/month based on eight A100 80GB GPU-hours (AWS ml.p4de.24xlarge on-demand ~$32/hr × 720 hrs). This is an infrastructure cost estimate, not a published API rate — verify current AWS pricing before budgeting.
- 2.TII's strategic focus has shifted to Falcon 3, Falcon H1, Falcon Arabic, and Falcon Perception — Falcon 180B is effectively legacy for new projects.
- 3.No fine-tuning or embeddings API exists for Falcon 180B.
- 4.No shared per-token API exists — no API pricing to publish.
- 5.Infrastructure cost for SageMaker/self-host: AWS ml.p4de.24xlarge (8× A100 80GB) on-demand ~$32/hour → approximately $23,040/month sustained. Reserved pricing is lower. This is an estimated calculation from AWS EC2 pricing, not a published API rate — verify at aws.amazon.com/ec2/pricing.
- 6.Effective per-token cost = infrastructure cost divided by throughput. Rough estimate: approximately $2-5 per MTok at scale depending on utilization (not a published figure — varies significantly with batch size, sequence length, and instance utilization).
- 7.For comparison: Qwen3-Max (recommended alternative) on DashScope at $1.20 input / $6.00 output per MTok with a 50% batch discount — no infrastructure overhead.
Limits verified against the TII (Technology Innovation Institute) docs, July 10, 2026.
not applicable (no shared API exists) vs the alternatives
Falcon 180B vs managed-API alternatives that eliminate the infrastructure overhead and licensing complexity of Falcon 180B deployment.
| Aspect | not applicable (no shared API exists) | Qwen3-Max | Llama 4 Maverick | Mixtral 8x22B |
|---|---|---|---|---|
| Hosted per-token API availability | none (no shared API; license restricts third-party hosting) | DashScope live | third-party hosts (Fireworks, DeepInfra) | legacy hosted (some third-party) |
| Parameter count | 180B (dense) | ~400B total MoE (Llama 4 Maverick) | 141B total MoE (Mixtral 8x22B) | comparable dense 180B |
| Context window (hosted) | n/a (no API; trained 2K-4K, some sources cite 8K — verify) | 262K (DashScope) | up to 1M (Fireworks) | 64K estimated |
| License (third-party hosting) | Falcon-180B TII License — requires separate TII permission for third-party hosting | Qwen3 License | Llama 4 Community License | Apache 2.0 |
| Input $/MTok (hosted) | not applicable (no API) | $1.20 (DashScope) | $0.15-$0.17 (Fireworks/DeepInfra) | legacy rates |
| Training data (tokens) | 3.5 trillion tokens | not published | not published | approximately 70B |
| Release date / recency | September 2023 (2+ years old) | 2026 (Qwen3-Max) | 2025 (Llama 4 Maverick) | 2023 (Mixtral 8x22B) |
| Self-host GPU memory requirement | 640GB FP16 (8×A100 80GB) / 320GB int4 (8×A100 40GB) | large MoE (Qwen3 dense smaller) | large MoE | large MoE |
Swipe the table sideways to see every model.
Hitting a 429? The playbook
The exact errors you'll see
Not applicable — no shared Falcon 180B API endpoint exists.ThrottlingException (AWS SageMaker — if your dedicated endpoint is undersized or receives traffic spikes beyond configured instance count)ModelError or InvocationError (SageMaker endpoint error when the model instance is OOM or unavailable)vLLM / TGI HTTP 429 (self-hosted inference server — standard HTTP rate limit if you implement request queuing)Why it happens & how to fix it
Searching for a Falcon 180B per-token shared API
No shared API exists due to the Falcon-180B TII License restriction on third-party hosting. Use SageMaker JumpStart to deploy a dedicated instance in your own AWS VPC, or self-host on your own GPU cluster.
SageMaker endpoint ThrottlingException due to undersized instance
Scale out the number of model instances on your SageMaker endpoint (Endpoint Configuration → variant instance count), or switch to SageMaker async inference for batch-style workloads that can tolerate latency.
Out of memory (OOM) during self-hosted inference
Reduce batch size to 1; switch from FP16 to int4 quantization (approximately halves memory from 640GB to 320GB, enabling 8×A100 40GB instead of 8×A100 80GB); use tensor parallelism with vLLM across all 8 GPUs.
License violation: serving Falcon 180B to third parties
Obtain a separate commercial hosting license from TII by contacting falconllm.tii.ae. Self-hosting for your own internal use is permitted under the Falcon-180B TII License; serving to external third parties is not without additional TII permission.
Retry strategy
No shared-API retry pattern applies to Falcon 180B. For SageMaker dedicated endpoints: use the AWS SDK's built-in retry configuration (max_attempts, retry_mode). For self-hosted vLLM or TGI inference servers: implement standard HTTP 429 retry with exponential backoff and jitter. If running SageMaker async inference, the SDK handles requeuing automatically.
1// Falcon 180B has no shared per-token API.2// SageMaker dedicated endpoint invocation with retry:3import {4 SageMakerRuntimeClient,5 InvokeEndpointCommand,6} from '@aws-sdk/client-sagemaker-runtime';78const client = new SageMakerRuntimeClient({9 region: process.env.AWS_REGION ?? 'us-east-1',10 maxAttempts: 5, // AWS SDK built-in retry11});1213async function invokeFalcon(prompt: string): Promise<string> {14 const payload = JSON.stringify({ inputs: prompt });15 let lastError: unknown;16 for (let attempt = 0; attempt < 5; attempt++) {17 try {18 const cmd = new InvokeEndpointCommand({19 EndpointName: process.env.FALCON_ENDPOINT_NAME ?? 'falcon-180b',20 ContentType: 'application/json',21 Body: Buffer.from(payload),22 });23 const result = await client.send(cmd);24 const text = new TextDecoder().decode(result.Body);25 return JSON.parse(text)[0]?.generated_text ?? text;26 } catch (err: any) {27 lastError = err;28 if (err?.name === 'ThrottlingException' && attempt < 4) {29 const wait = Math.min(60000, 1000 * Math.pow(2, attempt)) +30 Math.random() * 1000;31 console.warn(`ThrottlingException attempt ${attempt + 1}; wait ${wait}ms`);32 await new Promise((r) => setTimeout(r, wait));33 } else {34 throw err;35 }36 }37 }38 throw lastError;39}How to raise your limits
The ladder from the starter tier to enterprise — what each rung takes, and what it unlocks.
Evaluation (SageMaker JumpStart spot or HF Space)
Hours (JumpStart deployment provisioning)AWS Console → SageMaker → JumpStart → search 'Falcon 180B' → Deploy to ml.p4de.24xlarge spot instance. No shared demo exists — SageMaker is the lowest-friction evaluation path.
Unlocks: Dedicated instance for testing; no shared-API alternative; spot pricing reduces cost during evaluation phase
Production dedicated deployment
Days (procurement and provisioning)Deploy SageMaker ml.p4de.24xlarge reserved instance or procure and configure your own 8×A100 80GB cluster
Unlocks: Sustained inference at approximately $20K+/month infrastructure cost (reserved pricing lower than on-demand ~$23K); full control over throughput and SLA
Commercial third-party hosting license
Unknown (legal negotiation timeline; not a self-serve process)Contact TII via falconllm.tii.ae to obtain a separate commercial hosting license permitting third-party serving
Unlocks: Legal ability to serve Falcon 180B to external users or offer it as a service — not available self-serve as of July 2026
Cut your token spend
Seriously evaluate migrating to Qwen3-Max, Llama 4 Maverick, or newer TII models (Falcon 3 / H1)
Eliminates $20K+/month infrastructure overhead; replaces with $144/month managed API at comparable production scaleQwen3-Max on DashScope ($1.20/$6.00 per MTok, batch 50% off) or Llama 4 Maverick on Fireworks/DeepInfra eliminates the infrastructure cost, licensing complexity, and operational burden of Falcon 180B dedicated deployment. Falcon 3 and Falcon H1 are TII's newer model families and may have different API availability — verify at falconllm.tii.ae.
Use int4 quantization to halve GPU memory requirements
Reduces from 640GB (FP16) to approximately 320GB (int4) — enables 8×A100 40GB instead of 8×A100 80GBWith vLLM: specify quantization in the serve command. This enables use of the more available A100 40GB form factor and may reduce cloud infrastructure cost by 30-50% depending on provider pricing for 40GB vs 80GB variants.
Use SageMaker Inference Recommender before committing to on-demand pricing
Right-sizes the instance to actual throughput requirements before incurring sustained costsRun SageMaker Inference Recommender with representative traffic samples. It identifies the minimum instance size that meets your latency and throughput requirements, preventing over-provisioning at $32/hour.
Enable SageMaker async inference for batch-style workloads
Avoids endpoint under-provisioning during traffic spikes; decouples request volume from real-time capacityConfigure SageMaker async inference endpoint for workloads that can tolerate seconds to minutes of latency. Async inference queues requests and processes them as capacity allows, reducing the need to provision for peak traffic.
Set up SageMaker endpoint autoscaling based on InvocationsPerInstance
Reduces idle capacity cost during low-traffic periodsConfigure Application Auto Scaling on your SageMaker endpoint using the InvocationsPerInstance metric. Scale in during off-peak hours and scale out to handle traffic bursts, avoiding paying for idle instances at $32/hour.
Frequently asked questions
Does Falcon 180B have an API?
No shared per-token API exists for Falcon 180B as of July 2026. The Falcon-180B TII License restricts 'hosting use' — serving the model to third parties requires separate written permission from TII. This is why no major inference provider (Fireworks, Together AI, DeepInfra, Replicate) offers Falcon 180B access. The only options are deploying a dedicated instance via AWS SageMaker JumpStart (in your own VPC) or self-hosting on your own GPU cluster.
Why can't I find Falcon 180B on inference providers?
The Falcon-180B TII License explicitly restricts 'hosting use' — offering Falcon 180B as a shared service to others requires a separate commercial hosting license from TII. This makes it legally complex for inference providers to serve it, which is why providers like Fireworks, Together AI, and DeepInfra do not list it. Contact TII at falconllm.tii.ae if you need a commercial hosting license.
How much does running Falcon 180B cost?
There is no per-token API — you pay for infrastructure. A dedicated AWS ml.p4de.24xlarge instance (8×A100 80GB) runs approximately $32/hour on-demand, or around $23,000/month sustained. This is an estimated calculation from AWS EC2 pricing — verify current rates at aws.amazon.com/ec2/pricing. Reserved instances reduce this cost. For comparison: Qwen3-Max on DashScope handles 60M input / 12M output per month for $144.
What are the Falcon 180B GPU requirements?
At FP16 precision: approximately 640GB GPU memory, or roughly eight A100 80GB GPUs. At int4 quantization: approximately 320GB, enabling eight A100 40GB GPUs. Inference is typically run with tensor parallelism across all 8 GPUs using vLLM (vllm serve tiiuae/falcon-180B --tensor-parallel-size 8).
Can I use Falcon 180B commercially?
You can self-host Falcon 180B for your own internal commercial use under the Falcon-180B TII License (Apache 2.0 base with TII modifications). However, you cannot offer it as a hosted service to third parties without a separate commercial hosting license from TII. Contact falconllm.tii.ae for licensing inquiries.
What is the best Falcon 180B alternative with a proper API?
For most teams: Qwen3-Max on DashScope ($1.20/$6.00 per MTok, 262K context, 50% batch discount, managed API) or Llama 4 Maverick on third-party hosts ($0.15-$0.17/$0.65 per MTok, MoE architecture, active third-party support). Both eliminate the $20K+/month infrastructure cost and licensing complexity of Falcon 180B. RapidDev (rapidevelopers.com/contact) can help evaluate your specific workload requirements against available managed APIs.
Is Falcon 180B still a good model in 2026?
Falcon 180B was a strong performer when released in September 2023, trained on 3.5 trillion tokens. By July 2026, newer models (Qwen3-Max, Llama 4 Maverick, Falcon 3 / H1 from TII itself) offer better capability, longer context windows, and accessible managed APIs. Falcon 180B is effectively legacy and not recommended for new projects. TII's own strategic focus has shifted to Falcon 3, Falcon H1, Falcon Arabic, and Falcon Perception.
How do I deploy Falcon 180B on AWS SageMaker JumpStart?
Go to AWS Console → SageMaker → JumpStart → search for 'Falcon 180B' → click Deploy. SageMaker will provision an ml.p4de.24xlarge instance (or equivalent) within your VPC. You pay EC2 on-demand rates (~$32/hour). This is a dedicated deployment — you own the instance and all traffic runs in your AWS account, satisfying the TII License requirement for self-hosting rather than third-party hosting.
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