Gemini 2.5 Flash-Lite vs GPT-5.4 nano vs MiniMax-M2.7
Gemini 2.5 Flash-Lite comes out ahead, 71 to 68 and 61 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemini 2.5 Flash-Lite
71/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
OpenAIGPT-5.4 nano
68/100- ECI145.8
- Price$0.20 / $1.25
- Context400K
MiniMaxMiniMax-M2.7
61/100- ECI145.9
- Price$0.30 / $1.20
- Context205K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against GPT-5.4 nano (68) and MiniMax-M2.7 (61). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · GPT-5.4 nano 145.8 · Gemini 2.5 Flash-Lite 133.9
- Lowest priceGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · GPT-5.4 nano $0.463 · MiniMax-M2.7 $0.525 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · GPT-5.4 nano 400,000 · MiniMax-M2.7 204,800 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · GPT-5.4 nano: Text, Images · MiniMax-M2.7: Text
- Self-hostingMiniMax-M2.7Publishes downloadable weights
| Measure | Weight | Gemini 2.5 Flash-Lite | GPT-5.4 nano | MiniMax-M2.7 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 58 | 73 | 73 |
| Price | 25% | 86 | 66 | 63 |
| Inputs & features | 15% | 100 | 70 | 35 |
| Context window | 10% | 61 | 44 | 32 |
| Overall | 100% | 71/100 | 68/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 Flash-LiteGoogle | GPT-5.4 nanoOpenAI | MiniMax-M2.7MiniMax |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 133.9 | 145.8 | 145.9 (best) |
| ECI rank | #118 of 148 | #75 of 148 | #73 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 78.5% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 44.9% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 87.8% | — |
| SimpleQA VerifiedShort factual questions | — | 11.7% | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.20 | $0.30 |
| Output | $0.40 (best) | $1.25 | $1.20 |
| Cached input | $0.01 (best) | $0.02 | $0.06 |
| Blended (3:1) | $0.175 (best) | $0.463 | $0.525 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official OpenAI API | Official MiniMax (minimax.io) API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 400,000 tokens | 204,800 tokens |
| Max output | 65,536 tokens | 128,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | gemini-2.5-flash-lite | gpt-5.4-nano | MiniMax-M2.7 |
| API providers | 20 | 26 | 29 (best) |
| Released | Jun 17, 2025 | Mar 17, 2026 | Mar 18, 2026 |
| Knowledge cutoff | Jan 2025 | Aug 31, 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.5 Flash-Lite$1.80
- GPT-5.4 nano$4.50
- MiniMax-M2.7$5.40
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, GPT-5.4 nano or MiniMax-M2.7?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against GPT-5.4 nano (68) and MiniMax-M2.7 (61). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 2.5 Flash-Lite, GPT-5.4 nano or MiniMax-M2.7?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). GPT-5.4 nano costs $0.20 input / $1.25 output per million tokens (official OpenAI API price); MiniMax-M2.7 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Gemini 2.5 Flash-Lite versus $0.463 for GPT-5.4 nano (2.6× as much) and $0.525 for MiniMax-M2.7 (3× as much).
Which scores higher on benchmarks?
MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148), GPT-5.4 nano 145.8 (#75 of 148) and Gemini 2.5 Flash-Lite 133.9 (#118 of 148). The confidence ranges of the top two overlap (138.2–148.0 vs 143.2–147.7), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, GPT-5.4 nano and MiniMax-M2.7 yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5.4 nano and 204,800 for MiniMax-M2.7. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, GPT-5.4 nano up to 128,000, MiniMax-M2.7 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; GPT-5.4 nano accepts text and images; MiniMax-M2.7 accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
MiniMax-M2.7 publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite and GPT-5.4 nano is proprietary.
Which is newer?
MiniMax-M2.7 is the newest, released Mar 18, 2026. GPT-5.4 nano came out Mar 17, 2026; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, GPT-5.4 nano Aug 31, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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