Llama 3.3 70B Instruct vs Llama 4 Scout 17B-16E Instruct
Llama 3.3 70B Instruct (2025) and Llama 4 Scout 17B-16E Instruct (2025) are compact production models from AI at Meta. Llama 3.3 70B Instruct ships a 128k-token context window, while Llama 4 Scout 17B-16E Instruct ships a 10m-token context window. On pricing, Llama 4 Scout 17B-16E Instruct costs $0.08/1M input tokens versus $0.96/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 4 Scout 17B-16E Instruct is ~1100% cheaper at $0.08/1M; pay for Llama 3.3 70B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3.3 70B Instruct | Llama 4 Scout 17B-16E Instruct |
|---|---|---|
| Best for | general production evaluation | multimodal apps, long-context analysis, and provider-routed production |
| Decision fit | RAG, Long context, and Classification | Coding, RAG, and Agents |
| Context window | 128k | 10m |
| Cheapest output | $1.28/1M tokens | $0.30/1M tokens |
| Provider routes | 1 tracked | 12 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3.3 70B Instruct for RAG, Long context, and Classification.
- Llama 4 Scout 17B-16E Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Scout 17B-16E Instruct has the lower cheapest tracked output price at $0.30/1M tokens.
- Llama 4 Scout 17B-16E Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 4 Scout 17B-16E Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Llama 4 Scout 17B-16E Instruct for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.3 70B Instruct
$1,088
Cheapest tracked route/tier: AWS Bedrock
Llama 4 Scout 17B-16E Instruct
$139
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $949. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 4 Scout 17B-16E Instruct is $0.98/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Llama 4 Scout 17B-16E Instruct adds Vision and Multimodal in local capability data.
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 3.3 70B Instruct is $0.98/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-01 | 2025-04-05 |
| Context window | 128k | 10m |
| Parameters | 70B | 109B (17B active) |
| Architecture | - | mixture of experts |
| License | Llama 3 Community | Llama 4 Community |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2023-12 | 2024-08 |
Pricing and availability
| Pricing attribute | Llama 3.3 70B Instruct | Llama 4 Scout 17B-16E Instruct |
|---|---|---|
| Input price | $0.96/1M tokens | $0.08/1M tokens |
| Output price | $1.28/1M tokens | $0.30/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.3 70B Instruct | Llama 4 Scout 17B-16E Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Llama 4 Scout 17B-16E Instruct and multimodal input: Llama 4 Scout 17B-16E Instruct. Both models share structured outputs, 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.
For cost, Llama 3.3 70B Instruct lists $0.96/1M input and $1.28/1M output tokens on the cheapest tracked provider, while Llama 4 Scout 17B-16E Instruct lists $0.08/1M input and $0.30/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Scout 17B-16E Instruct lower by about $0.91 per million blended tokens. Availability is 1 providers versus 12, so concentration risk also matters.
Choose Llama 3.3 70B Instruct when provider fit are central to the workload. Choose Llama 4 Scout 17B-16E Instruct when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, Llama 3.3 70B Instruct or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct supports 10m tokens, while Llama 3.3 70B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 3.3 70B Instruct or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct is cheaper on tracked token pricing. Llama 3.3 70B Instruct costs $0.96/1M input and $1.28/1M output tokens. Llama 4 Scout 17B-16E Instruct costs $0.08/1M input and $0.30/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.3 70B Instruct or Llama 4 Scout 17B-16E Instruct open source?
Llama 3.3 70B Instruct is listed under Llama 3 Community. Llama 4 Scout 17B-16E Instruct is listed under Llama 4 Community. 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 vision, Llama 3.3 70B Instruct or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Llama 3.3 70B Instruct or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.3 70B Instruct and Llama 4 Scout 17B-16E Instruct?
Llama 3.3 70B Instruct is available on AWS Bedrock. Llama 4 Scout 17B-16E Instruct is available on Cloudflare Workers AI, OpenRouter, Together AI, Fireworks AI, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-07. Data sourced from public model cards and provider documentation.