LLM Reference

Llama 2 7B vs Nemotron 4 340B

Llama 2 7B (2023) and Nemotron 4 340B (2025) are compact production models from AI at Meta and NVIDIA AI. Llama 2 7B ships a 4k-token context window, while Nemotron 4 340B ships a 4k-token context window. On pricing, Llama 2 7B costs $0.20/1M input tokens versus $4.20/1M 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 2 7B is ~2000% cheaper at $0.20/1M; pay for Nemotron 4 340B only for provider fit.

Decision scorecard

Local evidence first
SignalLlama 2 7BNemotron 4 340B
Best forgeneral production evaluationprovider-routed production
Decision fitCoding and ClassificationClassification and JSON / Tool use
Context window4k4k
Cheapest output$0.20/1M tokens$4.20/1M tokens
Provider routes1 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama 2 7B when...
  • Llama 2 7B has the lower cheapest tracked output price at $0.20/1M tokens.
  • Local decision data tags Llama 2 7B for Coding and Classification.
Choose Nemotron 4 340B when...
  • Nemotron 4 340B has broader tracked provider coverage for fallback and procurement flexibility.
  • Nemotron 4 340B uniquely exposes Structured outputs in local model data.
  • Local decision data tags Nemotron 4 340B for Classification and JSON / Tool use.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Llama 2 7B

Llama 2 7B

$210

Cheapest tracked route/tier: Fireworks AI

Nemotron 4 340B

$4,410

Cheapest tracked route/tier: DeepInfra

Estimated monthly gap: $4,200. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Llama 2 7B -> Nemotron 4 340B
  • No overlapping tracked provider route is sourced for Llama 2 7B and Nemotron 4 340B; plan for SDK, billing, or endpoint changes.
  • Nemotron 4 340B is $4/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Nemotron 4 340B adds Structured outputs in local capability data.
Nemotron 4 340B -> Llama 2 7B
  • No overlapping tracked provider route is sourced for Nemotron 4 340B and Llama 2 7B; plan for SDK, billing, or endpoint changes.
  • Llama 2 7B is $4/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2023-07-182025-02-27
Context window4k4k
Parameters7B340B
Architecturedecoder onlydecoder only
LicenseLlama 2 CommunityNVIDIA Open Model
OpennessOpen weightsOpen weights
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff2022-09-

Pricing and availability

Pricing attributeLlama 2 7BNemotron 4 340B
Input price$0.20/1M tokens$4.20/1M tokens
Output price$0.20/1M tokens$4.20/1M tokens
Providers

Capabilities

CapabilityLlama 2 7BNemotron 4 340B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Nemotron 4 340B. 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 2 7B lists $0.20/1M input and $0.20/1M output tokens on the cheapest tracked provider, while Nemotron 4 340B lists $4.20/1M input and $4.20/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 2 7B lower by about $4 per million blended tokens. Availability is 1 providers versus 2, so concentration risk also matters.

Choose Llama 2 7B when provider fit and lower input-token cost are central to the workload. Choose Nemotron 4 340B 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which has a larger context window, Llama 2 7B or Nemotron 4 340B?

Llama 2 7B supports 4k tokens, while Nemotron 4 340B 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 2 7B or Nemotron 4 340B?

Llama 2 7B is cheaper on tracked token pricing. Llama 2 7B costs $0.20/1M input and $0.20/1M output tokens. Nemotron 4 340B costs $4.20/1M input and $4.20/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Llama 2 7B or Nemotron 4 340B open source?

Llama 2 7B is listed under Llama 2 Community. Nemotron 4 340B is listed under NVIDIA Open Model. 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 2 7B or Nemotron 4 340B?

Nemotron 4 340B 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 2 7B and Nemotron 4 340B?

Llama 2 7B is available on Fireworks AI. Nemotron 4 340B is available on NVIDIA NIM and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Llama 2 7B over Nemotron 4 340B?

Llama 2 7B is ~2000% cheaper at $0.20/1M; pay for Nemotron 4 340B only for provider fit. If your workload also depends on provider fit, start with Llama 2 7B; if it depends on provider fit, run the same evaluation with Nemotron 4 340B.

Continue comparing

Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.