Claude Opus 4.5 vs GPT-5.4
At a Glance
| Compare | Claude Opus 4.5Anthropic |  GPT-5.4OpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #27 of 4655.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.9–70.3 | #14 of 4672.8 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | #40 of 44$0.380 per LiveBench case | #36 of 44$0.274 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #36 of 3838.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 28.8–45.4 | #25 of 3850.1 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | $2.50Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $25.00Anthropic ↗ · Sep 3, 2026 | $15.00Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 200K | 1,050K |
| Model facts checked | Sep 3, 2026View model evidence → | Sep 3, 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 | Claude Opus 4.5 | GPT-5.4 |
|---|---|---|
| LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,462.2099% of row best · rating · claude-opus-4-5-20251101; 95% CI [1451.78988580, 1472.60655272]; votes 7981; rank 21 | 1,471.00100% of row best · rating · gpt-5.4; 95% CI [1464.96841782, 1477.04032901]; votes 33331; rank 14 |
| LMArena Search Arenasearch-2026-08-24-d25aabda0010 · arena_rating · leader | 1,179.6499% of row best · rating · claude-opus-4-5-search; 95% CI [1174.02872051, 1185.26030035]; votes 61573; rank 19 | 1,197.16100% of row best · rating · gpt-5.4-search; 95% CI [1191.73811150, 1202.57682579]; votes 110116; rank 16 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,447.08100% of row best · rating · claude-opus-4-5-20251101-high-32k; 95% CI [1443.17965746, 1450.98398333]; votes 36239; rank 49 | 1,452.64100% of row best · rating · gpt-5.4; 95% CI [1448.87114809, 1456.41035855]; votes 63526; rank 41 |
| LiveBench2026-06-25 · overall · leader | 77.3994% of row best · percent · claude-opus-4-5-20251101-thinking-64k-high-effort · 15,203 output tokens / case | 82.38100% of row best · percent · gpt-5.4-xhigh · 18,273 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 2 ties | 0 benchmark wins | 2 benchmark winsOverall lead |
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 | Claude Opus 4.5 | GPT-5.4 |
|---|---|---|
| Developer | Anthropic | OpenAI |
| Family | Claude 4 | Gpt 5 4 |
| Model | Claude Opus 4.5 | GPT-5.4 |
| Version | Claude Opus 4.5 | GPT-5.4 |
| Lifecycle | active | active |
| Released | 2025-11-24 | 2026-03-05 |
| Knowledge cutoff | 2025-05-01 | 2025-08-31 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 200K | 1,050K |
| 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 |
Claude Opus 4.5 Capabilities
GPT-5.4 Capabilities
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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 FAQs
Is Claude Opus 4.5 or GPT-5.4 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.5 and GPT-5.4, 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?+
Claude Opus 4.5 is $5.00 and GPT-5.4 is $2.50 per million tokens, so GPT-5.4 is cheaper on this metric. Claude Opus 4.5 is $25.00 and GPT-5.4 is $15.00 per million tokens, so GPT-5.4 is cheaper on this metric.
Which has a larger context window, Claude Opus 4.5 or GPT-5.4?+
GPT-5.4 has the larger sourced context window. Claude Opus 4.5 supports 200K and GPT-5.4 supports 1,050K.
Which performs better in benchmarks, Claude Opus 4.5 or GPT-5.4?+
GPT-5.4 leads the current overall benchmark count. The result uses 4 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Claude Opus 4.5 or GPT-5.4 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 is not marked open weight.
Can Claude Opus 4.5 and GPT-5.4 understand images?+
Claude Opus 4.5 is documented with image input; GPT-5.4 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?+
GPT-5.4 has the larger sourced maximum output: Claude Opus 4.5 supports 64K and GPT-5.4 supports 128K output tokens.
Do Claude Opus 4.5 and GPT-5.4 support reasoning and tool use?+
Claude Opus 4.5: reasoning, tool calling, and image input. GPT-5.4: 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?+
Claude Opus 4.5 has 1 sourced provider route; GPT-5.4 has 2, so GPT-5.4 has broader tracked availability.
Which offers better value, Claude Opus 4.5 or GPT-5.4?+
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.