LLM·Dex

GPT-5 nano vs Sonar Large

A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.

Updated

GPT-5 nano specs · Sonar Large specs
Verdict by category
  • PriceGPT-5 nano

    GPT-5 nano is roughly 2.5× cheaper on output tokens ($0.40 vs $1.00 per 1M).

  • Context windowGPT-5 nano

    GPT-5 nano accepts 400K tokens vs 127K, 3.1× the room for long documents and codebases.

  • BenchmarksTie

    No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.

  • ModalitiesGPT-5 nano

    GPT-5 nano supports 2 modalities (text, vision) vs 1 for Sonar Large.

  • OpennessTie

    Both are closed-weight, API-only.

On balance GPT-5 nano edges ahead, winning 3 of 5 categories against Sonar Large's 0. GPT-5 nano is roughly 2.5× cheaper on output tokens ($0.40 vs $1.00 per 1M). GPT-5 nano accepts 400K tokens vs 127K, 3.1× the room for long documents and codebases.

No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. They differ in modality coverage, GPT-5 nano handles text, vision while Sonar Large handles text, which can be the deciding factor before you even look at benchmarks. Both are closed-weight, API-only.

GPT-5 nano is the newer of the two, released 9 months after Sonar Large, which usually means a more recent knowledge cutoff and updated safety post-training. GPT-5 nano is usually picked for cheapest llm and fastest llm workloads, while Sonar Large sees more deployments in research agent and rag. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.

Side-by-side specs

SpecGPT-5 nanoSonar Large
ProviderOpenAIPerplexity
ReleasedAug 2025Nov 2024
Modalitiestext, visiontext
Context window400K tokens127K tokens
Max output128K tokens,
Input · 1M$0.050 / 1M tokens$1.00 / 1M tokens
Output · 1M$0.40 / 1M tokens$1.00 / 1M tokens
Knowledge cutoff2024-09,
Open weightsNoNo
API availableYesYes

Pricing at scale

What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.

  • Light usage, 100k in / 50k out per day$0.750 vs $4.50
  • Heavy usage, 1M in / 500k out per day$7.50 vs $45.00
  • RAG workload, 5M in / 200k out per day$9.90 vs $156

Light usage, 100k in / 50k out per day: $0.750 vs $4.50 per month, model A comes out ahead. Heavy usage, 1M in / 500k out per day: $7.50 vs $45.00 per month, model A comes out ahead. RAG workload, 5M in / 200k out per day: $9.90 vs $156 per month, model A comes out ahead.

Price calculator

Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.

  • GPT-5 nano$0.025
  • Sonar Large$0.150

Benchmarks compared

Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.

Benchmark scores not yet available. We only publish numbers we can source from official model cards or independent leaderboards, see methodology.
Pick GPT-5 nano if

GPT-5 nano fits when…

  • Lowest-cost OpenAI model with vision support
  • Fast P99 latency
  • Good enough for routing and classification
  • Cost-sensitive workloads, 2.5× cheaper than Sonar Large on output tokens.
  • Long-context tasks, handles 400K tokens vs 127K for Sonar Large.
Pick Sonar Large if

Sonar Large fits when…

  • Web-search grounded
  • Citation-first output
  • Cheap
Don't want either?

Consider GPT-5.5

OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.

Frequently asked

  • Is GPT-5 nano or Sonar Large cheaper?
    GPT-5 nano is cheaper at $0.40 / 1M tokens per million output tokens, vs $1.00 / 1M tokens for Sonar Large.
  • Which has the larger context window?
    GPT-5 nano accepts 400K tokens vs 127K for Sonar Large.
  • Is GPT-5 nano or Sonar Large better for coding?
    Both GPT-5 nano and Sonar Large are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.
  • Are either of these models open source?
    Neither model ships open weights, both are accessible only via their respective providers' APIs.
  • When were GPT-5 nano and Sonar Large released?
    GPT-5 nano was released by OpenAI on 2025-08-07. Sonar Large was released by Perplexity on 2024-11-19.
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