DeepSeek V4 Flash vs Llama 3.2 1B
DeepSeek V4 Flash (2026) and Llama 3.2 1B (2024) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek V4 Flash ships a 1M-token context window, while Llama 3.2 1B ships a 128K-token context window. On HumanEval, DeepSeek V4 Flash leads by 41.4 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek V4 Flash fits 8x more tokens; pick it for long-context work and Llama 3.2 1B for tighter calls.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Flash | Llama 3.2 1B |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | general production evaluation |
| Decision fit | Coding, RAG, and Agents | Coding, Long context, and Classification |
| Context window | 1M | 128K |
| Cheapest output | $0.12/1M tokens | $0.10/1M tokens |
| Provider routes | 5 tracked | 1 tracked |
| Shared benchmarks | HumanEval leader | 2 shared |
Decision tradeoffs
- DeepSeek V4 Flash holds a shared-benchmark lead on HumanEval, ahead by 41.4 points.
- DeepSeek V4 Flash has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V4 Flash has broader tracked provider coverage for fallback and route flexibility.
- DeepSeek V4 Flash uniquely exposes Reasoning, JSON / Tool use, and Structured outputs in local model data.
- Local decision data tags DeepSeek V4 Flash for Coding, RAG, and Agents.
- Llama 3.2 1B has the lower cheapest tracked output price at $0.10/1M tokens.
- Local decision data tags Llama 3.2 1B for Coding, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V4 Flash
$76.26
Cheapest tracked route/tier: OpenRouter
Llama 3.2 1B
$105
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $28.74. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for DeepSeek V4 Flash and Llama 3.2 1B; plan for SDK, billing, or endpoint changes.
- Llama 3.2 1B is $0.02/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, JSON / Tool use, and Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.2 1B and DeepSeek V4 Flash; plan for SDK, billing, or endpoint changes.
- DeepSeek V4 Flash is $0.02/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- DeepSeek V4 Flash adds Reasoning, JSON / Tool use, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2024-09-25 |
| Context window | 1M | 128K |
| Parameters | 284B | 1.23B |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | Llama 3 Community |
| Openness | Open source | Open weights |
| Weights | Available | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Pricing attribute | DeepSeek V4 Flash | Llama 3.2 1B |
|---|---|---|
| Input price |
| $0.10/1M tokens |
| Output price |
| $0.10/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Flash | Llama 3.2 1B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V4 Flash | Llama 3.2 1B |
|---|---|---|
| HumanEval | 69.5 | 28.1 |
| Massive Multitask Language Understanding | 88.7 | 54.2 |
Deep dive
On shared benchmark coverage, HumanEval has DeepSeek V4 Flash at 69.5 and Llama 3.2 1B at 28.1, with DeepSeek V4 Flash ahead by 41.4 points; Massive Multitask Language Understanding has DeepSeek V4 Flash at 88.7 and Llama 3.2 1B at 54.2, with DeepSeek V4 Flash ahead by 34.5 points. The largest visible gap is 41.4 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 reasoning mode: DeepSeek V4 Flash, JSON / Tool use: DeepSeek V4 Flash, JSON / Tool use: DeepSeek V4 Flash, and structured outputs: DeepSeek V4 Flash. 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 V4 Flash lists tiered pricing: Off-peak is $0.22/1M input and $0.66/1M output; Peak is $0.44/1M input and $1.32/1M output, while Llama 3.2 1B lists $0.10/1M input and $0.10/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V4 Flash lower by about $0.02 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 5 providers versus 1, so concentration risk also matters.
Choose DeepSeek V4 Flash when reasoning depth, larger context windows, and lower cheapest-tier input-token cost are central to the workload. Choose Llama 3.2 1B 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, DeepSeek V4 Flash or Llama 3.2 1B?
DeepSeek V4 Flash supports 1M tokens, while Llama 3.2 1B 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 V4 Flash or Llama 3.2 1B?
DeepSeek V4 Flash lists tiered pricing: Off-peak is $0.22/1M input and $0.66/1M output; Peak is $0.44/1M input and $1.32/1M output. Llama 3.2 1B lists $0.10/1M input and $0.10/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V4 Flash or Llama 3.2 1B open source?
DeepSeek V4 Flash is listed under MIT. Llama 3.2 1B 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 reasoning mode, DeepSeek V4 Flash or Llama 3.2 1B?
DeepSeek V4 Flash has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for JSON / Tool use, DeepSeek V4 Flash or Llama 3.2 1B?
DeepSeek V4 Flash has the clearer documented JSON / Tool use signal in this comparison. If JSON / Tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V4 Flash and Llama 3.2 1B?
DeepSeek V4 Flash is available on DeepSeek Platform, OpenRouter, Microsoft Foundry, Vercel AI Gateway, and Novita AI. Llama 3.2 1B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-10-12. Data sourced from public model cards and provider documentation.