Claude Opus 4.5 vs GPT-5.4 Nano
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | Claude Opus 4.5 | GPT-5.4 Nano |
|---|---|---|
| IntelligenceHigher is better · MM Intelligence v1.2 | UnrankedNot in the 22-model eligible cohort | #22 of 2214.7 score |
| CostLower is better · Published-token output estimate | #34 of 36$0.380 per LiveBench case | #13 of 36$0.058 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.0 | UnrankedNot in the 22-model eligible cohort | #21 of 2235.3 score |
Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.
Benchmark Performance
Available Benchmarks
| Benchmark | Claude Opus 4.5 | GPT-5.4 Nano |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,447.19100% of row best · rating · claude-opus-4-5-20251101-high-32k; 95% CI [1443.28922560, 1451.09589305]; votes 36271; rank 46 | 1,372.8795% of row best · rating · gpt-5.4-nano-high; 95% CI [1369.01004978, 1376.72255426]; votes 58562; rank 163 |
| LiveBench2026-06-25 · overall · leader | 77.39100% of row best · percent · claude-opus-4-5-20251101-thinking-64k-high-effort · 15,203 output tokens / case | 75.2797% of row best · percent · gpt-5.4-nano-xhigh · 46,179 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 2 benchmark winsOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Claude Opus 4.5 | GPT-5.4 Nano |
|---|---|---|
| Developer | Anthropic | OpenAI |
| Family | Claude 4 | Gpt 5 4 |
| Model | Claude Opus 4.5 | GPT-5.4 Nano |
| Version | Claude Opus 4.5 | GPT-5.4 Nano |
| Lifecycle | active | active |
| Released | 2025-11-24 | 2026-03-17 |
| Knowledge cutoff | 2025-05-01 | 2025-08-31 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 200K | 400K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Anthropic (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, structured_outputs, tools |
15 comparable fields · 8 material differences · Pair passes the primary-source comparison gate
Claude Opus 4.5 Capabilities
GPT-5.4 Nano Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
Claude Opus 4.5Anthropic | vs | GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs | Claude Opus 4.5Anthropic | family variantsimage, text |
Claude Opus 4.5Anthropic | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Claude Opus 4.5Anthropic | vs |  DeepSeek-V4-ProDeepSeek | cross-developer peerstext |
Claude Opus 4.5Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
Claude Opus 4.5Anthropic | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
Claude Opus 4.5Anthropic | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Claude Opus 4.5Anthropic | cross-developer peersimage, text |
Claude Opus 4.5Anthropic | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Claude Opus 4.5Anthropic | vs |  Hy4 previewTencent | cross-developer peerstext |
Claude Opus 4.5Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Opus 4.5Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.5 vs GPT-5.4 Nano FAQs
Is Claude Opus 4.5 or GPT-5.4 Nano better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.5 and GPT-5.4 Nano, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 4.5 or GPT-5.4 Nano?+
Claude Opus 4.5 is $5.00 and GPT-5.4 Nano is $0.20 per million tokens, so GPT-5.4 Nano is cheaper on this metric. Claude Opus 4.5 is $25.00 and GPT-5.4 Nano is $1.25 per million tokens, so GPT-5.4 Nano is cheaper on this metric.
Which has a larger context window, Claude Opus 4.5 or GPT-5.4 Nano?+
GPT-5.4 Nano has the larger sourced context window. Claude Opus 4.5 supports 200K and GPT-5.4 Nano supports 400K.
Which performs better in benchmarks, Claude Opus 4.5 or GPT-5.4 Nano?+
Claude Opus 4.5 leads the current overall benchmark count. The result uses 2 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Claude Opus 4.5 or GPT-5.4 Nano be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Opus 4.5 is not marked open weight; GPT-5.4 Nano is not marked open weight.
Can Claude Opus 4.5 and GPT-5.4 Nano understand images?+
Claude Opus 4.5 is documented with image input; GPT-5.4 Nano is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 4.5 or GPT-5.4 Nano?+
GPT-5.4 Nano has the larger sourced maximum output: Claude Opus 4.5 supports 64K and GPT-5.4 Nano supports 128K output tokens.
Do Claude Opus 4.5 and GPT-5.4 Nano support reasoning and tool use?+
Claude Opus 4.5: reasoning, tool calling, and image input. GPT-5.4 Nano: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 4.5 or GPT-5.4 Nano?+
Claude Opus 4.5 has 1 sourced provider route; GPT-5.4 Nano has 2, so GPT-5.4 Nano has broader tracked availability.
Which offers better value, Claude Opus 4.5 or GPT-5.4 Nano?+
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.