DeepSeek R1 0528 vs Gemini 2.5 Flash vs GPT OSS 120B
Gemini 2.5 Flash comes out ahead, 66 to 58 and 53 on our weighted score, though GPT OSS 120B is 3.2× cheaper per token.
DeepSeekDeepSeek R1 0528
53/100- ECI141.2
- Price$0.512 / $2.19
- Context164K
- Our pick
GoogleGemini 2.5 Flash
66/100- ECI140.6
- Price$0.30 / $2.50
- Context1.05M
OpenAIGPT OSS 120B
58/100- ECI139.8
- Price$0.15 / $0.60
- Context131K
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against GPT OSS 120B (58) and DeepSeek R1 0528 (53). It leads on inputs & features and context window. GPT OSS 120B 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 · GPT OSS 120B 139.8
- Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · 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 · GPT OSS 120B 131,072 tokens
- Widest inputsGemini 2.5 FlashDeepSeek R1 0528: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GPT OSS 120B: Text
- Self-hostingDeepSeek R1 0528 and GPT OSS 120BPublishes downloadable weights (MIT)
| Measure | Weight | DeepSeek R1 0528 | Gemini 2.5 Flash | GPT OSS 120B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 66 | 65 | 64 |
| Price | 25% | 49 | 51 | 74 |
| Inputs & features | 15% | 35 | 100 | 35 |
| Context window | 10% | 28 | 61 | 25 |
| Overall | 100% | 53/100 | 66/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek R1 0528DeepSeek | Gemini 2.5 FlashGoogle | GPT OSS 120BOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 141.2 (best) | 140.6 | 139.8 |
| ECI rank | #108 of 165 (best) | #110 of 165 | #114 of 165 |
| GPQA DiamondGraduate-level science questions | 76.3% (best) | — | 75.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.4% | — | 88.9% (best) |
| Price per million tokens | |||
| Input | $0.512 | $0.30 | $0.15 (best) |
| Output | $2.19 | $2.50 | $0.60 (best) |
| Cached input | — | $0.03 | — |
| Blended (3:1) | $0.932 | $0.85 | $0.263 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 16 providers | Official Google API | Median of 65 providers |
| Limits | |||
| Context window | 163,840 tokens | 1,048,576 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 65,536 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenMIT | Proprietary | Open |
| API model ID | — | gemini-2.5-flash | — |
| API providers | 16 | 32 | 67 (best) |
| Released | May 28, 2025 | Jun 17, 2025 | Aug 5, 2025 |
| Knowledge cutoff | — | Jan 2025 | 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 0528$9.50
- Gemini 2.5 Flash$8.00
- GPT OSS 120B$2.70
Which should you choose?
Which is better: DeepSeek R1 0528, Gemini 2.5 Flash or GPT OSS 120B?
Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against GPT OSS 120B (58) and DeepSeek R1 0528 (53). It leads on inputs & features and context window. GPT OSS 120B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek R1 0528, Gemini 2.5 Flash or GPT OSS 120B?
GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 65 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 $0.263 per million tokens for GPT OSS 120B versus $0.85 for Gemini 2.5 Flash (3.2× as much) and $0.932 for DeepSeek R1 0528 (3.6× 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 GPT OSS 120B 139.8 (#114 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, Gemini 2.5 Flash and GPT OSS 120B 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 GPT OSS 120B. Maximum output per response: DeepSeek R1 0528 up to 32,768, Gemini 2.5 Flash up to 65,536, GPT OSS 120B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
DeepSeek R1 0528 accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GPT OSS 120B accepts text. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek R1 0528 and GPT OSS 120B publishes its weights (MIT) and can be self-hosted; Gemini 2.5 Flash is proprietary.
Which is newer?
GPT OSS 120B is the newest, released Aug 5, 2025. Gemini 2.5 Flash came out Jun 17, 2025; DeepSeek R1 0528 came out May 28, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, GPT OSS 120B 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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