GPT-4.1 Nano vs Hy3
At a Glance
| Compare |  GPT-4.1 NanoOpenAI |  Hy3Tencent |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.050Openrouter ↗ · Sep 3, 2026 | $0.13Deepinfra ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $0.20Openrouter ↗ · Sep 3, 2026 | $0.528Openrouter ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 1,048K | 262K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | GPT-4.1 Nano | Hy3 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,284.7289% of row best · rating · gpt-4.1-nano-2025-04-14; 95% CI [1277.08013307, 1292.36659971]; votes 6103; rank 250 | 1,440.58100% of row best · rating · hy3; 95% CI [1433.39024152, 1447.77894384]; votes 8047; rank 65 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | GPT-4.1 Nano | Hy3 |
|---|---|---|
| Developer | OpenAI | Tencent |
| Family | Gpt 4 1 | Hy3 |
| Model | GPT-4.1 Nano | Hy3 |
| Version | GPT-4.1 Nano | Hy3 |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | 2024-06-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,048K | 262K |
| Total parameters | Unknown | 298.8B |
| Active parameters | Unknown | 21B |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Openai (Standard), Openrouter (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, tools | chat, generation, tools |
GPT-4.1 Nano Capabilities
Hy3 Capabilities
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Primary Evidence
Sources and Freshness
Questions
GPT-4.1 Nano vs Hy3 FAQs
Is GPT-4.1 Nano or Hy3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-4.1 Nano and Hy3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-4.1 Nano or Hy3?+
GPT-4.1 Nano is $0.050 and Hy3 is $0.13 per million tokens, so GPT-4.1 Nano is cheaper on this metric. GPT-4.1 Nano is $0.20 and Hy3 is $0.528 per million tokens, so GPT-4.1 Nano is cheaper on this metric.
Which has a larger context window, GPT-4.1 Nano or Hy3?+
GPT-4.1 Nano has the larger sourced context window. GPT-4.1 Nano supports 1,048K and Hy3 supports 262K.
Which performs better in benchmarks, GPT-4.1 Nano or Hy3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can GPT-4.1 Nano or Hy3 be self-hosted?+
Hy3 is the only model in this pair currently marked as self-hostable. GPT-4.1 Nano is not marked open weight; Hy3 is open weight.
Can GPT-4.1 Nano and Hy3 understand images?+
GPT-4.1 Nano is documented with image input; Hy3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-4.1 Nano or Hy3?+
Neither has a larger sourced maximum output. GPT-4.1 Nano is 33K and Hy3 is —.
Do GPT-4.1 Nano and Hy3 support reasoning and tool use?+
GPT-4.1 Nano: tool calling and image input. Hy3: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-4.1 Nano or Hy3?+
GPT-4.1 Nano has 2 sourced provider routes; Hy3 has 3, so Hy3 has broader tracked availability.
Which offers better value, GPT-4.1 Nano or Hy3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.