Gemini 2.5 Flash-Lite vs MiniMax-M2 Her vs Qwen3 Coder Next
Gemini 2.5 Flash-Lite comes out ahead, 85 to 51 and 45 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemini 2.5 Flash-Lite
85/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
MiniMaxMiniMax-M2 Her
45/100- ECI—
- Price$0.30 / $1.20
- Context66K
Alibaba (Qwen)Qwen3 Coder Next
51/100- ECI—
- Price$0.20 / $1.20
- Context262K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against Qwen3 Coder Next (51) and MiniMax-M2 Her (45). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · Qwen3 Coder Next $0.45 · MiniMax-M2 Her $0.525 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Qwen3 Coder Next 262,144 · MiniMax-M2 Her 65,536 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · MiniMax-M2 Her: Text · Qwen3 Coder Next: Text
- Self-hostingQwen3 Coder NextPublishes downloadable weights
| Measure | Weight | Gemini 2.5 Flash-Lite | MiniMax-M2 Her | Qwen3 Coder Next |
|---|---|---|---|---|
| Price | 50% | 86 | 63 | 66 |
| Inputs & features | 30% | 100 | 35 | 35 |
| Context window | 20% | 61 | 12 | 37 |
| Overall | 100% | 85/100 | 45/100 | 51/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 Flash-LiteGoogle | MiniMax-M2 HerMiniMax | Qwen3 Coder NextAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 133.9 | — | — |
| ECI rank | #118 of 148 | — | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.30 | $0.20 |
| Output | $0.40 (best) | $1.20 | $1.20 |
| Cached input | $0.01 | — | — |
| Blended (3:1) | $0.175 (best) | $0.525 | $0.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Median of 4 providers | Median of 11 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 65,536 tokens | 262,144 tokens |
| Max output | 65,536 tokens (best) | 2,048 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | gemini-2.5-flash-lite | — | — |
| API providers | 20 (best) | 4 | 11 |
| Released | Jun 17, 2025 | Jan 23, 2026 | Feb 3, 2026 |
| Knowledge cutoff | Jan 2025 | — | Sep 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
- MiniMax-M2 Her$5.40
- Qwen3 Coder Next$4.40
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, MiniMax-M2 Her or Qwen3 Coder Next?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against Qwen3 Coder Next (51) and MiniMax-M2 Her (45). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Gemini 2.5 Flash-Lite, MiniMax-M2 Her or Qwen3 Coder Next?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). Qwen3 Coder Next costs $0.20 input / $1.20 output per million tokens (median across 11 API providers); MiniMax-M2 Her costs $0.30 input / $1.20 output per million tokens (median across 4 API providers). 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 $0.45 for Qwen3 Coder Next (2.6× as much) and $0.525 for MiniMax-M2 Her (3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Flash-Lite has an ECI of 133.9, MiniMax-M2 Her has not been scored yet and Qwen3 Coder Next has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, MiniMax-M2 Her and Qwen3 Coder Next yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. 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 262,144 for Qwen3 Coder Next and 65,536 for MiniMax-M2 Her. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, MiniMax-M2 Her up to 2,048, Qwen3 Coder Next up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; MiniMax-M2 Her accepts text; Qwen3 Coder Next accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Qwen3 Coder Next publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite and MiniMax-M2 Her is proprietary.
Which is newer?
Qwen3 Coder Next is the newest, released Feb 3, 2026. MiniMax-M2 Her came out Jan 23, 2026; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, Qwen3 Coder Next Sep 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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