DeepSeek-R1-Distill-Qwen-32B vs Llama 4 Maverick 17B Instruct vs Gemini 2.0 Flash
Gemini 2.0 Flash comes out ahead, 56 to 47 and 45 on our weighted score, and it is the cheaper option too.
DeepSeekDeepSeek-R1-Distill-Qwen-32B
45/100- ECI—
- Price—
- Context131K
MetaLlama 4 Maverick 17B Instruct
47/100- ECI132.3
- Price$0.245 / $0.838
- Context1M
- Our pick
GoogleGemini 2.0 Flash
56/100- ECI134.7
- Price$0.10 / $0.42
- Context1.05M
Gemini 2.0 Flash is our pick
Gemini 2.0 Flash is the better all-round choice, scoring 56/100 against Llama 4 Maverick 17B Instruct (47) and DeepSeek-R1-Distill-Qwen-32B (45). It leads on inputs & features. DeepSeek-R1-Distill-Qwen-32B wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because DeepSeek-R1-Distill-Qwen-32B has no Capabilities Index score yet.
- CapabilityDeepSeek-R1-Distill-Qwen-32BShared benchmarks: DeepSeek-R1-Distill-Qwen-32B 59.9% · Gemini 2.0 Flash 47.6% · Llama 4 Maverick 17B Instruct 43.8%
- Lowest priceGemini 2.0 FlashGemini 2.0 Flash $0.18 · Llama 4 Maverick 17B Instruct $0.393 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
- Longest contextGemini 2.0 FlashGemini 2.0 Flash 1,048,576 · Llama 4 Maverick 17B Instruct 1,000,000 · DeepSeek-R1-Distill-Qwen-32B 131,072 tokens
- Widest inputsGemini 2.0 FlashDeepSeek-R1-Distill-Qwen-32B: Text · Llama 4 Maverick 17B Instruct: Text, Images · Gemini 2.0 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingDeepSeek-R1-Distill-Qwen-32B and Llama 4 Maverick 17B InstructPublishes downloadable weights
| Measure | Weight | DeepSeek-R1-Distill-Qwen-32B | Llama 4 Maverick 17B Instruct | Gemini 2.0 Flash |
|---|---|---|---|---|
| CapabilityShared benchmarks | 67% | 60 | 44 | 48 |
| Inputs & features | 20% | 10 | 50 | 80 |
| Context window | 13% | 25 | 60 | 61 |
| Overall | 100% | 45/100 | 47/100 | 56/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1-Distill-Qwen-32BDeepSeek | Llama 4 Maverick 17B InstructMeta | Gemini 2.0 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 132.3 | 134.7 (best) |
| ECI rank | — | #135 of 165 | #130 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 64.1% | 67.0% (best) | 64.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 55.6% (best) | 20.6% | 31.1% |
| Price per million tokens | |||
| Input | — | $0.245 | $0.10 (best) |
| Output | — | $0.838 | $0.42 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.393 | $0.18 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 16 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,000,000 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens (best) | 16,384 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | — | — |
| API providers | — | 16 (best) | 2 |
| Released | Jan 20, 2025 | Apr 5, 2025 | Dec 11, 2024 |
| Knowledge cutoff | — | Aug 2024 | Jun 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-R1-Distill-Qwen-32B—
- Llama 4 Maverick 17B Instruct$4.13
- Gemini 2.0 Flash$1.84
Which should you choose?
Which is better: DeepSeek-R1-Distill-Qwen-32B, Llama 4 Maverick 17B Instruct or Gemini 2.0 Flash?
Gemini 2.0 Flash is the better all-round choice, scoring 56/100 against Llama 4 Maverick 17B Instruct (47) and DeepSeek-R1-Distill-Qwen-32B (45). It leads on inputs & features. DeepSeek-R1-Distill-Qwen-32B wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because DeepSeek-R1-Distill-Qwen-32B has no Capabilities Index score yet.
Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, Llama 4 Maverick 17B Instruct or Gemini 2.0 Flash?
Gemini 2.0 Flash is cheaper at $0.10 input / $0.42 output per million tokens (median across 1 API provider). Llama 4 Maverick 17B Instruct costs $0.245 input / $0.838 output per million tokens (median across 16 API providers). At a typical mix of three input tokens to one output token, that is $0.18 per million tokens for Gemini 2.0 Flash versus $0.393 for Llama 4 Maverick 17B Instruct (2.2× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): DeepSeek-R1-Distill-Qwen-32B 59.9%, Gemini 2.0 Flash 47.6% and Llama 4 Maverick 17B Instruct 43.8%. On individual benchmarks: GPQA Diamond — Llama 4 Maverick 17B Instruct 67.0%, DeepSeek-R1-Distill-Qwen-32B 64.1%, Gemini 2.0 Flash 64.1%; OTIS Mock AIME 2024–2025 — DeepSeek-R1-Distill-Qwen-32B 55.6%, Gemini 2.0 Flash 31.1%, Llama 4 Maverick 17B Instruct 20.6%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1-Distill-Qwen-32B, Llama 4 Maverick 17B Instruct and Gemini 2.0 Flash yet, so there is no like-for-like coding score. On overall capability, DeepSeek-R1-Distill-Qwen-32B leads, which tends to carry over to coding, but test on your own codebase. Note that DeepSeek-R1-Distill-Qwen-32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Gemini 2.0 Flash 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-R1-Distill-Qwen-32B. Maximum output per response: DeepSeek-R1-Distill-Qwen-32B up to 32,768, Llama 4 Maverick 17B Instruct up to 16,384, Gemini 2.0 Flash up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1-Distill-Qwen-32B accepts text; Llama 4 Maverick 17B Instruct accepts text and images; Gemini 2.0 Flash accepts text, images, PDFs, audio and video. Gemini 2.0 Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek-R1-Distill-Qwen-32B and Llama 4 Maverick 17B Instruct publishes its weights and can be self-hosted; Gemini 2.0 Flash is proprietary.
Which is newer?
Llama 4 Maverick 17B Instruct is the newest, released Apr 5, 2025. DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025; Gemini 2.0 Flash came out Dec 11, 2024. Knowledge cutoff: Llama 4 Maverick 17B Instruct Aug 2024, Gemini 2.0 Flash Jun 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 Nov 2, 2026.
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