# August's flagship model releases: GPT-5, Opus 4.1, gpt-oss and DeepSeek V3.1 compared

- **Published:** 2025-09-03
- **Updated:** 2026-10-12
- **Category:** Models & Benchmarks
- **Author:** Sinthetix
- **URL:** https://sinthetix.com/blog/august-flagship-model-releases-compared

> Four significant model releases landed in August 2025. What each claims, what is verified, and what the near-tie on coding benchmarks does and does not mean.

August was unusually dense with model releases. Within three weeks, Anthropic shipped Claude Opus 4.1, OpenAI shipped both GPT-5 and its first open-weight models since GPT-2, and DeepSeek released a hybrid reasoning model under an MIT license. For a buyer, the useful question is not which one "won" but what each release changes about cost, deployment options and risk.

**Key takeaways**

- On SWE-bench Verified, GPT-5 (74.9%) and Claude Opus 4.1 (74.5%) are effectively tied, and the two vendors report them under different conditions.
- OpenAI's gpt-oss models are Apache 2.0 licensed and small enough to run on a single 80 GB GPU (120B) or 16 GB of memory (20B).
- DeepSeek V3.1 is MIT licensed, with API pricing that drops sharply on cache hits.
- Vendor-reported hallucination and "deception" figures use different baselines and graders, so they are not directly comparable across releases.

## The releases

### Claude Opus 4.1 (August 5)

Anthropic positions Opus 4.1 as an upgrade to Opus 4 for agentic tasks, real-world coding and reasoning, and reports 74.5% on SWE-bench Verified, measured without extended thinking [1]. Pricing is described only as "the same as Opus 4" [1]. It is available to paid Claude users, in Claude Code, via the API, Amazon Bedrock and Google Cloud's Vertex AI [1]. Anthropic also said it planned "substantially larger improvements" in the coming weeks [1].

### GPT-5 (August 7)

OpenAI describes GPT-5 as a unified system that routes between a faster model and a deeper reasoning model depending on the query; the secondary coverage notes OpenAI has not confirmed whether this is one model or several orchestrated ones [2]. Reported API pricing is $1.25 per million input tokens and $10.00 per million output tokens, with GPT-5 mini and nano priced lower and cached input at one-tenth of the live input price [2]. Reported SWE-bench Verified: 74.9%, versus 69.1% for o3 [2].

OpenAI's GPT-5 system card reports that on prompts representative of ChatGPT production conversations, gpt-5-main produced 44% fewer responses with at least one major factual error than GPT-4o, and gpt-5-thinking 78% fewer than o3, as scored by an LLM grader with web access that agreed with human reviewers 75% of the time [5]. It also reports that a chain-of-thought monitor flagged deception in about 4.8% of o3 responses and about 2.1% of gpt-5-thinking responses on a representative set of conversations [5]. These are first-party figures, each against a different baseline, and the system card notes that the 74.9% SWE-bench result comes from the launch post and was run at default API verbosity [5].

### gpt-oss (August 5)

OpenAI released two open-weight models under the Apache 2.0 license: the 120B model (117 billion parameters, 5.1 billion active per token) and the 20B (21 billion, 3.6 billion active) [3]. The larger runs on a single 80 GB H100; the smaller fits in 16 GB of VRAM [3]. Context is 128K tokens, reasoning effort is set to low, medium or high in the system prompt, and the models lack vision [3]. OpenAI says the 120B performs roughly on par with its proprietary o4-mini and the 20B is similar to o3-mini [3].

### DeepSeek V3.1 (August 21)

DeepSeek V3.1 has 671 billion total parameters with 37 billion active, a 128,000-token window in both modes, and switches between a "think" mode and a "non-think" mode [4]. Code and weights are MIT licensed [4]. Per The Decoder, Artificial Analysis scored it 60 on its intelligence index in reasoning mode versus 59 for R1, and noted it does not support function calling in reasoning mode, a limit for agent workflows [4].

## Side by side

| Model | Release | Access | Reported SWE-bench Verified | License / pricing note |
| --- | --- | --- | --- | --- |
| Claude Opus 4.1 [1] | Aug 5 | API, Bedrock, Vertex AI | 74.5% (no extended thinking) | Same price as Opus 4 |
| GPT-5 [2] | Aug 7 | OpenAI API / ChatGPT | 74.9% | $1.25 in / $10.00 out per M tokens |
| gpt-oss-120b [3] | Aug 5 | Open weights | not stated | Apache 2.0 |
| DeepSeek V3.1 [4] | Aug 21 | Open weights, API | not stated | MIT |

DeepSeek's API pricing, starting September 5, is $0.07 per million input tokens on a cache hit, $0.56 on a cache miss and $1.68 for output [4].

**SWE-bench Verified, vendor-reported**

Different vendors, different evaluation setups

Unit: %

| Category | SWE-bench Verified |
| --- | --- |
| OpenAI o3 | 69.1% |
| Claude Opus 4.1 | 74.5% |
| GPT-5 | 74.9% |

*o3 and GPT-5 figures as reported in \[2\]; the Opus 4.1 figure (74.5%, no extended thinking) is from Anthropic \[1\]. Setups are not identical. Source: [2], Gradient Flow*

## How to read this

The gap between 74.5% and 74.9% is smaller than the variance you should expect from harness choices, tool setups and run counts. A critic quoted in coverage of GPT-5 made a related point, noting the gain over the previous state of the art was only 0.4% [2]. What differentiates these releases for a business is less the benchmark and more the operating model: closed models with usage pricing, or open weights you can host yourself under permissive licenses [3][4].

The open-weight options matter for data-handling constraints. A 20B model that fits in 16 GB can run on a single workstation, and a 120B model on one 80 GB accelerator [3]. Neither claims frontier-level capability; OpenAI's own comparison is to o4-mini and o3-mini [3].

## Practical implication

Treat public benchmark gaps of a point or less as ties, and run your own task-level evaluation on a few hundred of your real cases before switching providers. If data residency or per-token cost is the constraint, the August open-weight releases make self-hosting a credible option to price out.

## Sources

1. [Claude Opus 4.1](https://www.anthropic.com/news/claude-opus-4-1), Anthropic, 2025-08-05
2. [GPT-5: key features and capabilities](https://gradientflow.com/gpt-5/), Gradient Flow, 2025-08-07
3. [OpenAI makes good on its name, launches first open weights language models since GPT-2](https://www.theregister.com/2025/08/05/openai_open_gpt/), The Register, 2025-08-05
4. [DeepSeek's first hybrid model V3.1 outperforms its R1 reasoning model on benchmarks](https://the-decoder.com/deepseeks-first-hybrid-model-v3-1-outperforms-its-r1-reasoning-model-on-benchmarks/), The Decoder, 2025-08-21
5. [GPT-5 System Card](https://cdn.openai.com/gpt-5-system-card.pdf), OpenAI, 2025-08-07

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