Gemini 2.5 Flash vs GPT-5.4
At a Glance
| Compare |  Gemini 2.5 FlashGoogle DeepMind |  GPT-5.4OpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #14 of 4672.8 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #36 of 44$0.274 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #25 of 3850.1 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.30Google AI ↗ · Aug 29, 2026 | $2.50Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $2.50Google AI ↗ · Aug 29, 2026 | $15.00Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,050K |
| Model facts checked | Aug 29, 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 | Gemini 2.5 Flash | GPT-5.4 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,417.2798% of row best · rating · gemini-2.5-flash; 95% CI [1414.83704531, 1419.70406968]; votes 122732; rank 116 | 1,452.64100% of row best · rating · gpt-5.4; 95% CI [1448.87114809, 1456.41035855]; votes 63526; rank 41 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,235.9896% of row best · rating · gemini-2.5-flash; 95% CI [1231.30819372, 1240.64679816]; votes 58893; rank 64 | 1,292.51100% of row best · rating · gpt-5.4; 95% CI [1285.77825721, 1299.23452617]; votes 21188; rank 22 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 72.1784% of row best · points · Gemini 2.5 Flash · 4,399 output tokens / case | 85.60100% of row best · points · GPT-5.4 (xhigh) · 10,941 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 2 benchmark winsNo 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 | Gemini 2.5 Flash | GPT-5.4 |
|---|---|---|
| Developer | Google DeepMind | OpenAI |
| Family | Gemini 2 5 | Gpt 5 4 |
| Model | Gemini 2.5 Flash | GPT-5.4 |
| Version | Gemini 2.5 Flash | GPT-5.4 |
| Lifecycle | active | active |
| Released | Unknown | 2026-03-05 |
| Knowledge cutoff | 2025-01-01 | 2025-08-31 |
| Input modalities | Text, Image, Video, Audio | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 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 | Google AI (Standard), Google Gemini (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
Gemini 2.5 Flash Capabilities
GPT-5.4 Capabilities
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|---|---|---|---|
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 DeepSeek-V4.1-FlashDeepSeek | vs | Gemini 2.5 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 2.5 FlashGoogle DeepMind | vs | Grok 4.6xAI | cross-developer peerstext |
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Gemini 2.5 FlashGoogle DeepMind | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | Gemini 2.5 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 2.5 FlashGoogle DeepMind | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Gemini 2.5 FlashGoogle DeepMind | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Gemini 2.5 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 2.5 FlashGoogle DeepMind | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 2.5 Flash vs GPT-5.4 FAQs
Is Gemini 2.5 Flash or GPT-5.4 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 2.5 Flash and GPT-5.4, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 2.5 Flash or GPT-5.4?+
Gemini 2.5 Flash is $0.30 and GPT-5.4 is $2.50 per million tokens, so Gemini 2.5 Flash is cheaper on this metric. Gemini 2.5 Flash is $2.50 and GPT-5.4 is $15.00 per million tokens, so Gemini 2.5 Flash is cheaper on this metric.
Which has a larger context window, Gemini 2.5 Flash or GPT-5.4?+
GPT-5.4 has the larger sourced context window. Gemini 2.5 Flash supports 1,049K and GPT-5.4 supports 1,050K.
Which performs better in benchmarks, Gemini 2.5 Flash or GPT-5.4?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Gemini 2.5 Flash or GPT-5.4 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Gemini 2.5 Flash is not marked open weight; GPT-5.4 is not marked open weight.
Can Gemini 2.5 Flash and GPT-5.4 understand images?+
Gemini 2.5 Flash 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, Gemini 2.5 Flash or GPT-5.4?+
GPT-5.4 has the larger sourced maximum output: Gemini 2.5 Flash supports 66K and GPT-5.4 supports 128K output tokens.
Do Gemini 2.5 Flash and GPT-5.4 support reasoning and tool use?+
Gemini 2.5 Flash: 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, Gemini 2.5 Flash or GPT-5.4?+
Gemini 2.5 Flash has 2 sourced provider routes; GPT-5.4 has 2, a tie.
Which offers better value, Gemini 2.5 Flash 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.