DeepSeek R1 0528 vs Qwen3 30B A3B vs Gemini 2.5 Flash
Gemini 2.5 Flash comes out ahead, 66 to 57 and 53 on our weighted score, though Qwen3 30B A3B is 4.3× cheaper per token.
DeepSeekDeepSeek R1 0528
53/100- ECI141.2
- Price$0.512 / $2.19
- Context164K
Alibaba (Qwen)Qwen3 30B A3B
57/100- ECI136.2
- Price$0.108 / $0.475
- Context131K
- Our pick
GoogleGemini 2.5 Flash
66/100- ECI140.6
- Price$0.30 / $2.50
- Context1.05M
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against Qwen3 30B A3B (57) and DeepSeek R1 0528 (53). It leads on inputs & features and context window. Qwen3 30B A3B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek R1 0528Capabilities Index (ECI): DeepSeek R1 0528 141.2 · Gemini 2.5 Flash 140.6 · Qwen3 30B A3B 136.2
- Lowest priceQwen3 30B A3BQwen3 30B A3B $0.20 · Gemini 2.5 Flash $0.85 · DeepSeek R1 0528 $0.932 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · DeepSeek R1 0528 163,840 · Qwen3 30B A3B 131,072 tokens
- Widest inputsGemini 2.5 FlashDeepSeek R1 0528: Text · Qwen3 30B A3B: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingDeepSeek R1 0528 and Qwen3 30B A3BPublishes downloadable weights (MIT)
| Measure | Weight | DeepSeek R1 0528 | Qwen3 30B A3B | Gemini 2.5 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 66 | 59 | 65 |
| Price | 25% | 49 | 80 | 51 |
| Inputs & features | 15% | 35 | 35 | 100 |
| Context window | 10% | 28 | 25 | 61 |
| Overall | 100% | 53/100 | 57/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek R1 0528DeepSeek | Qwen3 30B A3BAlibaba (Qwen) | Gemini 2.5 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 141.2 (best) | 136.2 | 140.6 |
| ECI rank | #108 of 165 (best) | #126 of 165 | #110 of 165 |
| GPQA DiamondGraduate-level science questions | 76.3% (best) | 61.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.4% (best) | 62.8% | — |
| Price per million tokens | |||
| Input | $0.512 | $0.108 (best) | $0.30 |
| Output | $2.19 | $0.475 (best) | $2.50 |
| Cached input | — | — | $0.03 |
| Blended (3:1) | $0.932 | $0.20 (best) | $0.85 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 16 providers | Median of 14 providers | Official Google API |
| Limits | |||
| Context window | 163,840 tokens | 131,072 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 16,384 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenMIT | Open | Proprietary |
| API model ID | — | — | gemini-2.5-flash |
| API providers | 16 | 14 | 32 (best) |
| Released | May 28, 2025 | Apr 28, 2025 | Jun 17, 2025 |
| Knowledge cutoff | — | — | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek R1 0528$9.50
- Qwen3 30B A3B$2.03
- Gemini 2.5 Flash$8.00
Which should you choose?
Which is better: DeepSeek R1 0528, Qwen3 30B A3B or Gemini 2.5 Flash?
Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against Qwen3 30B A3B (57) and DeepSeek R1 0528 (53). It leads on inputs & features and context window. Qwen3 30B A3B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek R1 0528, Qwen3 30B A3B or Gemini 2.5 Flash?
Qwen3 30B A3B is cheaper at $0.108 input / $0.475 output per million tokens (median across 14 API providers). Gemini 2.5 Flash costs $0.30 input / $2.50 output per million tokens (official Google API price); DeepSeek R1 0528 costs $0.512 input / $2.19 output per million tokens (median across 16 API providers). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for Qwen3 30B A3B versus $0.85 for Gemini 2.5 Flash (4.3× as much) and $0.932 for DeepSeek R1 0528 (4.7× as much).
Which scores higher on benchmarks?
DeepSeek R1 0528 scores higher on the Capabilities Index (ECI): DeepSeek R1 0528 141.2 (#108 of 165), Gemini 2.5 Flash 140.6 (#110 of 165) and Qwen3 30B A3B 136.2 (#126 of 165). The confidence ranges of the top two overlap (139.0–142.9 vs 138.4–142.1), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek R1 0528, Qwen3 30B A3B and Gemini 2.5 Flash yet, so there is no like-for-like coding score. On overall capability, DeepSeek R1 0528 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 has the largest context window at 1,048,576 tokens, against 163,840 for DeepSeek R1 0528 and 131,072 for Qwen3 30B A3B. Maximum output per response: DeepSeek R1 0528 up to 32,768, Qwen3 30B A3B up to 16,384, Gemini 2.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
DeepSeek R1 0528 accepts text; Qwen3 30B A3B accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek R1 0528 and Qwen3 30B A3B publishes its weights (MIT) and can be self-hosted; Gemini 2.5 Flash is proprietary.
Which is newer?
Gemini 2.5 Flash is the newest, released Jun 17, 2025. DeepSeek R1 0528 came out May 28, 2025; Qwen3 30B A3B came out Apr 28, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 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 Nov 2, 2026.
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