DeepSeek-V3 vs Gemini 2.5 Flash-Lite vs Llama 4 Maverick 17B Instruct
Gemini 2.5 Flash-Lite comes out ahead, 71 to 58 and 50 on our weighted score, and it is the cheaper option too.
DeepSeek
DeepSeek-V3
50/100- ECI132.3
- Price$0.32 / $1.10
- Context131K
- Our pick
Google
Gemini 2.5 Flash-Lite
71/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
Meta
Llama 4 Maverick 17B Instruct
58/100- ECI132.2
- Price$0.321 / $0.91
- Context1M
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against Llama 4 Maverick 17B Instruct (58) and DeepSeek-V3 (50). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 2.5 Flash-LiteCapabilities Index (ECI): Gemini 2.5 Flash-Lite 133.9 · DeepSeek-V3 132.3 · Llama 4 Maverick 17B Instruct 132.2
- Lowest priceGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · Llama 4 Maverick 17B Instruct $0.468 · DeepSeek-V3 $0.515 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Llama 4 Maverick 17B Instruct 1,000,000 · DeepSeek-V3 131,072 tokens
- Widest inputsGemini 2.5 Flash-LiteDeepSeek-V3: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Llama 4 Maverick 17B Instruct: Text, Images
- Self-hostingDeepSeek-V3 and Llama 4 Maverick 17B InstructPublishes downloadable weights (DeepSeek Model License)
| Measure | Weight | DeepSeek-V3 | Gemini 2.5 Flash-Lite | Llama 4 Maverick 17B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 56 | 58 | 56 |
| Price | 25% | 64 | 86 | 66 |
| Inputs & features | 15% | 25 | 100 | 50 |
| Context window | 10% | 24 | 61 | 60 |
| Overall | 100% | 50/100 | 71/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 132.3 | 133.9 (best) | 132.2 |
| ECI rank | #121 of 148 | #118 of 148 (best) | #122 of 148 |
| GPQA DiamondGraduate-level science questions | 56.5% | — | 67.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 15.8% | — | 20.6% (best) |
| Price per million tokens | |||
| Input | $0.32 | $0.10 (best) | $0.321 |
| Output | $1.10 | $0.40 (best) | $0.91 |
| Cached input | — | $0.01 | — |
| Blended (3:1) | $0.515 | $0.175 (best) | $0.468 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 5 providers | Official Google API | Median of 6 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 8,192 tokens | 65,536 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenDeepSeek Model License | Proprietary | Open |
| API model ID | — | gemini-2.5-flash-lite | — |
| API providers | 5 | 20 (best) | 6 |
| Released | Dec 26, 2024 | Jun 17, 2025 | Apr 5, 2025 |
| Knowledge cutoff | — | Jan 2025 | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
DeepSeek-V3$5.40
Gemini 2.5 Flash-Lite$1.80
Llama 4 Maverick 17B Instruct$5.03
Which should you choose?
Which is better: DeepSeek-V3, Gemini 2.5 Flash-Lite or Llama 4 Maverick 17B Instruct?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against Llama 4 Maverick 17B Instruct (58) and DeepSeek-V3 (50). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-V3, Gemini 2.5 Flash-Lite or Llama 4 Maverick 17B Instruct?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). Llama 4 Maverick 17B Instruct costs $0.321 input / $0.91 output per million tokens (median across 6 API providers); DeepSeek-V3 costs $0.32 input / $1.10 output per million tokens (median across 5 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 $0.468 for Llama 4 Maverick 17B Instruct (2.7× as much) and $0.515 for DeepSeek-V3 (2.9× as much).
Which scores higher on benchmarks?
Gemini 2.5 Flash-Lite scores higher on the Capabilities Index (ECI): Gemini 2.5 Flash-Lite 133.9 (#118 of 148), DeepSeek-V3 132.3 (#121 of 148) and Llama 4 Maverick 17B Instruct 132.2 (#122 of 148). The confidence ranges of the top two overlap (129.8–136.3 vs 127.5–135.5), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-V3, Gemini 2.5 Flash-Lite and Llama 4 Maverick 17B Instruct yet, so there is no like-for-like coding score. On overall capability, Gemini 2.5 Flash-Lite 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 1,000,000 for Llama 4 Maverick 17B Instruct and 131,072 for DeepSeek-V3. Maximum output per response: DeepSeek-V3 up to 8,192, Gemini 2.5 Flash-Lite up to 65,536, Llama 4 Maverick 17B Instruct up to 16,384 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-V3 accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Llama 4 Maverick 17B Instruct accepts text and images. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
DeepSeek-V3 and Llama 4 Maverick 17B Instruct publishes its weights (DeepSeek Model License) and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
Gemini 2.5 Flash-Lite is the newest, released Jun 17, 2025. Llama 4 Maverick 17B Instruct came out Apr 5, 2025; DeepSeek-V3 came out Dec 26, 2024. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, Llama 4 Maverick 17B Instruct Aug 2024.
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.