DeepSeek V3 0324 vs Llama 3.2 1B Instruct
DeepSeek V3 0324 (2025) and Llama 3.2 1B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek V3 0324 ships a 160k-token context window, while Llama 3.2 1B Instruct ships a 128k-token context window. On Google-Proof Q&A, DeepSeek V3 0324 leads by 62.0 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 3.2 1B Instruct is ~900% cheaper at $0.03/1M; pay for DeepSeek V3 0324 only for long-context analysis.
Decision scorecard
Local evidence first| Signal | DeepSeek V3 0324 | Llama 3.2 1B Instruct |
|---|---|---|
| Best for | provider-routed production | provider-routed production |
| Decision fit | Coding, Agents, and Long context | Coding, RAG, and Long context |
| Context window | 160k | 128k |
| Cheapest output | $1.12/1M tokens | $0.20/1M tokens |
| Provider routes | 3 tracked | 7 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 2 rows |
Decision tradeoffs
- DeepSeek V3 0324 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 62.0 points.
- DeepSeek V3 0324 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags DeepSeek V3 0324 for Coding, Agents, and Long context.
- Llama 3.2 1B Instruct has the lower cheapest tracked output price at $0.20/1M tokens.
- Llama 3.2 1B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3.2 1B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3.2 1B Instruct for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V3 0324
$496
Cheapest tracked route/tier: Novita AI
Llama 3.2 1B Instruct
$71.85
Cheapest tracked route/tier: Cloudflare Workers AI
Estimated monthly gap: $424. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Llama 3.2 1B Instruct is $0.92/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Llama 3.2 1B Instruct adds Structured outputs in local capability data.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- DeepSeek V3 0324 is $0.92/1M 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.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-24 | 2024-09-25 |
| Context window | 160k | 128k |
| Parameters | 671B | 1.23B |
| Architecture | decoder only | decoder only |
| License | MIT(OSI) | Llama 3 Community |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Pricing attribute | DeepSeek V3 0324 | Llama 3.2 1B Instruct |
|---|---|---|
| Input price | $0.27/1M tokens | $0.03/1M tokens |
| Output price | $1.12/1M tokens | $0.20/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3 0324 | Llama 3.2 1B Instruct |
|---|---|---|
| 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 |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V3 0324 | Llama 3.2 1B Instruct |
|---|---|---|
| Google-Proof Q&A | 87.6 | 25.6 |
| HumanEval | 85.5 | 28.1 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has DeepSeek V3 0324 at 87.6 and Llama 3.2 1B Instruct at 25.6, with DeepSeek V3 0324 ahead by 62.0 points; HumanEval has DeepSeek V3 0324 at 85.5 and Llama 3.2 1B Instruct at 28.1, with DeepSeek V3 0324 ahead by 57.4 points. The largest visible gap is 62.0 points on Google-Proof Q&A, 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 3.2 1B 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, DeepSeek V3 0324 lists $0.27/1M input and $1.12/1M output tokens on the cheapest tracked provider, while Llama 3.2 1B Instruct lists $0.03/1M input and $0.20/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 1B Instruct lower by about $0.45 per million blended tokens. Availability is 3 providers versus 7, so concentration risk also matters.
Choose DeepSeek V3 0324 when long-context analysis and larger context windows are central to the workload. Choose Llama 3.2 1B Instruct when provider fit, lower input-token cost, 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
Which has a larger context window, DeepSeek V3 0324 or Llama 3.2 1B Instruct?
DeepSeek V3 0324 supports 160k tokens, while Llama 3.2 1B 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, DeepSeek V3 0324 or Llama 3.2 1B Instruct?
Llama 3.2 1B Instruct is cheaper on tracked token pricing. DeepSeek V3 0324 costs $0.27/1M input and $1.12/1M output tokens. Llama 3.2 1B Instruct costs $0.03/1M input and $0.20/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3 0324 or Llama 3.2 1B Instruct open source?
DeepSeek V3 0324 is listed under MIT. Llama 3.2 1B Instruct is listed under Llama 3 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 structured outputs, DeepSeek V3 0324 or Llama 3.2 1B Instruct?
Llama 3.2 1B 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 DeepSeek V3 0324 and Llama 3.2 1B Instruct?
DeepSeek V3 0324 is available on Fireworks AI, Microsoft Foundry, and Novita AI. Llama 3.2 1B Instruct is available on Cloudflare Workers AI, OpenRouter, Fireworks AI, NVIDIA NIM, and Bitdeer AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick DeepSeek V3 0324 over Llama 3.2 1B Instruct?
Llama 3.2 1B Instruct is ~900% cheaper at $0.03/1M; pay for DeepSeek V3 0324 only for long-context analysis. If your workload also depends on long-context analysis, start with DeepSeek V3 0324; if it depends on provider fit, run the same evaluation with Llama 3.2 1B Instruct.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.