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DeepSeek Math 7B Instruct vs Llama 3.1 70B Instruct

DeepSeek Math 7B Instruct (2024) and Llama 3.1 70B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek Math 7B Instruct ships a not-yet-sourced context window, while Llama 3.1 70B Instruct ships a 128K-token context window. On HumanEval, Llama 3.1 70B Instruct leads by 5.2 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama 3.1 70B Instruct is safer overall; choose DeepSeek Math 7B Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalDeepSeek Math 7B InstructLlama 3.1 70B Instruct
Decision fitCoding and ClassificationCoding, RAG, and Long context
Context window128K
Cheapest output-$0.4/1M tokens
Provider routes0 tracked11 tracked
Shared benchmarks3 rowsHumanEval leader

Decision tradeoffs

Choose DeepSeek Math 7B Instruct when...
  • Local decision data tags DeepSeek Math 7B Instruct for Coding and Classification.
Choose Llama 3.1 70B Instruct when...
  • Llama 3.1 70B Instruct leads the largest shared benchmark signal on HumanEval by 5.2 points.
  • Llama 3.1 70B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Llama 3.1 70B Instruct uniquely exposes Structured outputs in local model data.
  • Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

DeepSeek Math 7B Instruct

Unavailable

No complete token price in local provider data

Llama 3.1 70B Instruct

$420

Cheapest tracked route: Hyperbolic AI Inference

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

DeepSeek Math 7B Instruct -> Llama 3.1 70B Instruct
  • No overlapping tracked provider route is sourced for DeepSeek Math 7B Instruct and Llama 3.1 70B Instruct; plan for SDK, billing, or endpoint changes.
  • Llama 3.1 70B Instruct adds Structured outputs in local capability data.
Llama 3.1 70B Instruct -> DeepSeek Math 7B Instruct
  • No overlapping tracked provider route is sourced for Llama 3.1 70B Instruct and DeepSeek Math 7B Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2024-02-052024-07-23
Context window128K
Parameters7B70B
Architecturedecoder onlydecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff--

Pricing and availability

Pricing attributeDeepSeek Math 7B InstructLlama 3.1 70B Instruct
Input price-$0.4/1M tokens
Output price-$0.4/1M tokens
Providers-

Capabilities

CapabilityDeepSeek Math 7B InstructLlama 3.1 70B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo

Benchmarks

BenchmarkDeepSeek Math 7B InstructLlama 3.1 70B Instruct
HumanEval78.984.1
Massive Multitask Language Understanding75.986.0
HellaSwag90.194.2

Deep dive

On shared benchmark coverage, HumanEval has DeepSeek Math 7B Instruct at 78.9 and Llama 3.1 70B Instruct at 84.1, with Llama 3.1 70B Instruct ahead by 5.2 points; Massive Multitask Language Understanding has DeepSeek Math 7B Instruct at 75.9 and Llama 3.1 70B Instruct at 86, with Llama 3.1 70B Instruct ahead by 10.1 points; HellaSwag has DeepSeek Math 7B Instruct at 90.1 and Llama 3.1 70B Instruct at 94.2, with Llama 3.1 70B Instruct ahead by 4.1 points. The largest visible gap is 10.1 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 3.1 70B 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.

Pricing coverage is uneven: DeepSeek Math 7B Instruct has no token price sourced yet and Llama 3.1 70B Instruct has $0.4/1M input tokens. Provider availability is 0 tracked routes versus 11. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose DeepSeek Math 7B Instruct when provider fit are central to the workload. Choose Llama 3.1 70B Instruct 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 DeepSeek Math 7B Instruct or Llama 3.1 70B Instruct open source?

DeepSeek Math 7B Instruct is listed under Open Source. Llama 3.1 70B Instruct 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, DeepSeek Math 7B Instruct or Llama 3.1 70B Instruct?

Llama 3.1 70B 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 Math 7B Instruct and Llama 3.1 70B Instruct?

DeepSeek Math 7B Instruct is available on the tracked providers still being sourced. Llama 3.1 70B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick DeepSeek Math 7B Instruct over Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct is safer overall; choose DeepSeek Math 7B Instruct when provider fit matters. If your workload also depends on provider fit, start with DeepSeek Math 7B Instruct; if it depends on provider fit, run the same evaluation with Llama 3.1 70B Instruct.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.