Falcon 180B vs Llama 2 70B Chat
Falcon 180B (2023) and Llama 2 70B Chat (2023) are compact production models from Technology Innovation Institute (TII) and AI at Meta. Falcon 180B ships a not-yet-sourced context window, while Llama 2 70B Chat ships a 4K-token context window. On Massive Multitask Language Understanding, Falcon 180B leads by 15.3 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Falcon 180B is safer overall; choose Llama 2 70B Chat when provider fit matters.
Decision scorecard
Local evidence first| Signal | Falcon 180B | Llama 2 70B Chat |
|---|---|---|
| Decision fit | Coding and Classification | Classification and JSON / Tool use |
| Context window | — | 4K |
| Cheapest output | - | $1.5/1M tokens |
| Provider routes | 2 tracked | 14 tracked |
| Shared benchmarks | Massive Multitask Language Understanding leader | 1 rows |
Decision tradeoffs
- Falcon 180B leads the largest shared benchmark signal on Massive Multitask Language Understanding by 15.3 points.
- Local decision data tags Falcon 180B for Coding and Classification.
- Llama 2 70B Chat has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 2 70B Chat has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 2 70B Chat uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 2 70B Chat for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Falcon 180B
Unavailable
No complete token price in local provider data
Llama 2 70B Chat
$775
Cheapest tracked route: Databricks Foundation Model Serving
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on Alibaba Cloud PAI-EAS and Scale AI GenAI Platform; start route-level A/B tests there.
- Llama 2 70B Chat adds Structured outputs in local capability data.
- Provider overlap exists on Alibaba Cloud PAI-EAS and Scale AI GenAI Platform; start route-level A/B tests there.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-11-28 | 2023-07-18 |
| Context window | — | 4K |
| Parameters | 180B | 70B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Falcon 180B | Llama 2 70B Chat |
|---|---|---|
| Input price | - | $0.5/1M tokens |
| Output price | - | $1.5/1M tokens |
| Providers |
Capabilities
| Capability | Falcon 180B | Llama 2 70B Chat |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
| Benchmark | Falcon 180B | Llama 2 70B Chat |
|---|---|---|
| Massive Multitask Language Understanding | 84.2 | 68.9 |
Deep dive
On shared benchmark coverage, Massive Multitask Language Understanding has Falcon 180B at 84.2 and Llama 2 70B Chat at 68.9, with Falcon 180B ahead by 15.3 points. The largest visible gap is 15.3 points on Massive Multitask Language Understanding, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on structured outputs: Llama 2 70B Chat. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: Falcon 180B has no token price sourced yet and Llama 2 70B Chat has $0.5/1M input tokens. Provider availability is 2 tracked routes versus 14. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Falcon 180B when provider fit are central to the workload. Choose Llama 2 70B Chat when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Is Falcon 180B or Llama 2 70B Chat open source?
Falcon 180B is listed under Apache 2.0. Llama 2 70B Chat is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Falcon 180B or Llama 2 70B Chat?
Llama 2 70B Chat has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Falcon 180B and Llama 2 70B Chat?
Falcon 180B is available on Alibaba Cloud PAI-EAS and Scale AI GenAI Platform. Llama 2 70B Chat is available on Databricks Foundation Model Serving, Microsoft Foundry, GCP Vertex AI, Alibaba Cloud PAI-EAS, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Falcon 180B over Llama 2 70B Chat?
Falcon 180B is safer overall; choose Llama 2 70B Chat when provider fit matters. If your workload also depends on provider fit, start with Falcon 180B; if it depends on provider fit, run the same evaluation with Llama 2 70B Chat.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.