deepseek-v4-pro vs gpt-oss-120b
gpt-oss-120b is 1.2× cheaper on input than deepseek-v4-pro.
| deepseek-v4-pro | gpt-oss-120b | |
|---|---|---|
| Input / 1M | $0.435 | $0.35 |
| Cached input / 1M | $0.004 | — |
| Output / 1M | $0.87 | $0.75 |
| Context window | 1M | 131K |
| Max output | 8K | 33K |
| Provider | DeepSeek | Cerebras |
| Vision | No | No |
| Tool calling | Yes | Yes |
| Token count | estimated | estimated |
Capability for the money
Independent measurement · Artificial Analysis · read 2026-08-11Not the same tier: deepseek-v4-pro leads gpt-oss-120b by 30.4 points on tool use (τ²-bench), for 1.2× the price.
Following instructions
extraction, classification, sticking to a format
IFBenchdeepseek-v4-pro +7.5
Tool use
multi-step agent work against real tools
τ²-benchdeepseek-v4-pro +30.4
Hard reasoning
graduate-level science and multi-step analysis
GPQA Diamonddeepseek-v4-pro +10.6
Averaged over the benchmarks both models sat, deepseek-v4-pro returns 160.3 points of pass rate per dollar of blended price against 157.8 — the ratio that decides whether the dearer model earns its rate.
Each figure is a pass rate: the share of that test set the model answered correctly, measured by a third party rather than self-reported by the lab. Rows are different tests of different difficulty, so compare a model against the other model, not one row against the next. No published coding score for one of these models, so that lens is omitted. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.
Which to pick
- Cheaper input: gpt-oss-120b
- Cheaper output: gpt-oss-120b
- Larger context: deepseek-v4-pro
- Better at following instructions: deepseek-v4-pro (76.5% vs 69.0% on IFBench)
- Better at tool use: deepseek-v4-pro (96.2% vs 65.8% on τ²-bench)
- Better at hard reasoning: deepseek-v4-pro (88.8% vs 78.2% on GPQA Diamond)
List price is not production cost. Output length, cache hit rate, retries and task quality move the real number more than the headline rate does — price your own prompt on the token ledger before deciding.
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