gpt-oss-120b vs mistral-medium-3-5
gpt-oss-120b is 4.3× cheaper on input than mistral-medium-3-5.
| gpt-oss-120b | mistral-medium-3-5 | |
|---|---|---|
| Input / 1M | $0.35 | $1.50 |
| Cached input / 1M | — | — |
| Output / 1M | $0.75 | $7.50 |
| Context window | 131K | 262K |
| Max output | 33K | 262K |
| Provider | Cerebras | Mistral |
| Vision | No | Yes |
| Tool calling | Yes | Yes |
| Token count | estimated | estimated |
Capability for the money
Independent measurement · Artificial Analysis · read 2026-08-11Not the same tier: mistral-medium-3-5 leads gpt-oss-120b by 28.4 points on tool use (τ²-bench), for 6.7× the price. They are level on following instructions (IFBench) and hard reasoning (GPQA Diamond), so the premium only pays off on tool use work.
Following instructions
extraction, classification, sticking to a format
IFBenchgpt-oss-120b +0.2
Tool use
multi-step agent work against real tools
τ²-benchmistral-medium-3-5 +28.4
Hard reasoning
graduate-level science and multi-step analysis
GPQA Diamondgpt-oss-120b +3.4
Averaged over the benchmarks both models sat, gpt-oss-120b returns 157.8 points of pass rate per dollar of blended price against 26.4 — 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: mistral-medium-3-5
- Better at following instructions: gpt-oss-120b (69.0% vs 68.8% on IFBench)
- Better at tool use: mistral-medium-3-5 (65.8% vs 94.2% on τ²-bench)
- Better at hard reasoning: gpt-oss-120b (78.2% vs 74.8% 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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