Llama 3 8B Instruct vs Phi-3 Mini 4k
Llama 3 8B Instruct (2024) and Phi-3 Mini 4k (2024) are compact production models from AI at Meta and Microsoft Research. Llama 3 8B Instruct ships a 8k-token context window, while Phi-3 Mini 4k ships a 4k-token context window. On MMLU PRO, Phi-3 Mini 4k leads by 5.2 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 3 8B Instruct is ~67% cheaper at $0.03/1M; pay for Phi-3 Mini 4k only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3 8B Instruct | Phi-3 Mini 4k |
|---|---|---|
| Best for | provider-routed production | provider-routed production |
| Decision fit | Coding, Classification, and JSON / Tool use | Coding and Classification |
| Context window | 8k | 4k |
| Cheapest output | $0.04/1M tokens | $0.25/1M tokens |
| Provider routes | 17 tracked | 4 tracked |
| Shared benchmarks | 6 rows | MMLU PRO leader |
Decision tradeoffs
- Llama 3 8B Instruct holds a shared-benchmark lead on Google-Proof Q&A, ahead by 3.9 points.
- Llama 3 8B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3 8B Instruct has the lower cheapest tracked output price at $0.04/1M tokens.
- Llama 3 8B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3 8B Instruct uniquely exposes Structured outputs in local model data.
- Phi-3 Mini 4k holds a shared-benchmark lead on MMLU PRO, ahead by 5.2 points.
- Local decision data tags Phi-3 Mini 4k for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3 8B Instruct
$34.00
Cheapest tracked route/tier: OpenRouter
Phi-3 Mini 4k
$103
Cheapest tracked route/tier: Replicate API
Estimated monthly gap: $68.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Microsoft Foundry, NVIDIA NIM, and Baseten API; start route-level A/B tests there.
- Phi-3 Mini 4k is $0.21/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on Baseten API, NVIDIA NIM, and Microsoft Foundry; start route-level A/B tests there.
- Llama 3 8B Instruct is $0.21/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Llama 3 8B Instruct adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2024-04-23 |
| Context window | 8k | 4k |
| Parameters | 8B | 3.8B |
| Architecture | decoder only | decoder only |
| License | Llama 3 Community | MIT(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2023-03 | 2023-10 |
Pricing and availability
| Pricing attribute | Llama 3 8B Instruct | Phi-3 Mini 4k |
|---|---|---|
| Input price | $0.03/1M tokens | $0.05/1M tokens |
| Output price | $0.04/1M tokens | $0.25/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3 8B Instruct | Phi-3 Mini 4k |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3 8B Instruct | Phi-3 Mini 4k |
|---|---|---|
| MMLU PRO | 40.5 | 45.7 |
| Google-Proof Q&A | 44.8 | 40.9 |
| HumanEval | 68.2 | 59.8 |
| Instruction-Following Evaluation | 59.5 | 45.0 |
| Massive Multitask Language Understanding | 76.9 | 68.2 |
| HellaSwag | 91.1 | 87.1 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3 8B Instruct at 40.5 and Phi-3 Mini 4k at 45.7, with Phi-3 Mini 4k ahead by 5.2 points; Google-Proof Q&A has Llama 3 8B Instruct at 44.8 and Phi-3 Mini 4k at 40.9, with Llama 3 8B Instruct ahead by 3.9 points; HumanEval has Llama 3 8B Instruct at 68.2 and Phi-3 Mini 4k at 59.8, with Llama 3 8B Instruct ahead by 8.4 points. The largest visible gap is 8.4 points on HumanEval, 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 3 8B Instruct. 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.
For cost, Llama 3 8B Instruct lists $0.03/1M input and $0.04/1M output tokens on the cheapest tracked provider, while Phi-3 Mini 4k lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 8B Instruct lower by about $0.08 per million blended tokens. Availability is 17 providers versus 4, so concentration risk also matters.
Choose Llama 3 8B Instruct when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Phi-3 Mini 4k when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 3 8B Instruct or Phi-3 Mini 4k?
Llama 3 8B Instruct supports 8k tokens, while Phi-3 Mini 4k supports 4k 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 8B Instruct or Phi-3 Mini 4k?
Llama 3 8B Instruct is cheaper on tracked token pricing. Llama 3 8B Instruct costs $0.03/1M input and $0.04/1M output tokens. Phi-3 Mini 4k costs $0.05/1M input and $0.25/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 8B Instruct or Phi-3 Mini 4k open source?
Llama 3 8B Instruct is listed under Llama 3 Community. Phi-3 Mini 4k is listed under MIT. 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, Llama 3 8B Instruct or Phi-3 Mini 4k?
Llama 3 8B Instruct 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 Llama 3 8B Instruct and Phi-3 Mini 4k?
Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API (Deprecated), Fireworks AI, and Alibaba Cloud PAI-EAS. Phi-3 Mini 4k is available on Microsoft Foundry, NVIDIA NIM, Baseten API, and Replicate API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3 8B Instruct over Phi-3 Mini 4k?
Llama 3 8B Instruct is ~67% cheaper at $0.03/1M; pay for Phi-3 Mini 4k only for provider fit. If your workload also depends on long-context analysis, start with Llama 3 8B Instruct; if it depends on provider fit, run the same evaluation with Phi-3 Mini 4k.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.